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IMAGE DATA PROCESSING OR GENERATION, IN GENERAL (specially adapted for particular applications, see the relevant subclasses, e.g. G06K, G09G, H04N)
Definition statement
This subclass/group covers:
  • General purpose image data processing.
  • Geometric image transformations in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image.
  • Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image.
  • Image analysis, e.g. from bit-mapped to non bit-mapped.
  • Image coding, e.g. from bit-mapped to non bit-mapped.
  • Two Dimensional image generation.
  • Animation.
  • Three Dimensional image rendering.
  • Three-dimensional modelling, e.g. data description of 3D objects.
  • Manipulating 3D models or images for computer graphics.
Relationship between large subject matter areas

G06T is the function place for image data processing or generation. Image data processing or generation specially adapted for particular application is classified in the relevant subclass, e.g. G06K 9/00, H04N

References relevant to classification in this subclass
This subclass/group does not cover:
Photogrammetry or videogrammetry
Computer-aided design
Reading or recognising printed or written characters or recognising patterns, e.g. fingerprints, which is covered by subclass
Modification of image data to allow display using multiple viewports
Circuits for generating functions for visual indicators
Arrangements or circuits for control of indicating devices
Scanning of documents or the like in pictorial communication
Informative references
Attention is drawn to the following places, which may be of interest for search:
Apparatus for radiation diagnosis
Aspects of games using an electronically generated display having two or more dimensions
Measuring, by optical means, length, thickness or similar linear dimensions, angles, areas, irregularities of surfaces or contours
Pattern Recognition
Coding, decoding or code conversion
Pictorial communication, television systems
Special rules of classification within this subclass

G06T1/40 is not used. Its subject-matter is covered by G06T 1/20.

G06T 11/80 is not used for classification as well. Its subject-matter is classified in G06F 3/00 and subgroups.

Whenever possible, additional information should be classified using one or more of the Indexing Codes from the range of G06T.

The following list of symbols from the series G06T200/00 are for allocation to documents within the whole range of G06T except G06T 9/00:

Indexing scheme for image data processing or generation, in general - Not used for classification
involving 3D image data - processing of 3D image data, i.e. voxels; relevant for G06T 3/00, G06T 5/00, G06T 7/00 or G06T 11/00;
involving all processing steps from image acquisition to 3D model generation - complete systems from acquisition to modelling
involving antialiasing - dejagging, staircase effect
involving adaptation to the client's capabilities - adapting the colour or resolution of an image to the client's capabilities
involving computational photography
involving graphical user interfaces [GUIs]
involving image processing hardware - relevant for groups not directly related to hardware; not used in G06T 1/20, G06T 1/60, G06T 15/005
involving image mosaicing - image mosaicing, panoramic images
Review paper; Tutorial; Survey - basic documents describing the state of the art.

There are further series of symbols for G06T whose use is reserved to particular maingroups or ranges of maingroups and whose full list and description are given in the FCRs of the respective maingroups:

G06T201/00 for G06T 1/0021 only

G06T207/00 for G06T 5/00 and G06T 7/00 only

G06T209/00 for G06T 9/00 only

G06T210/00 for G06T 11/00 to G06T 19/00 only; see list below

S06T211/4xx for G06T 11/003 only

G06T213/00 for G06T 13/00 only;

G06T215/00 for G06T 15/00 only;

S06T219/0xx for G06T 19/00 only;

S06T219/20XX for G06T 19/20 only

Symbols from the series G06T210/00 for allocation in the range of G06T 11/00 to G06T 19/00 only:

Indexing scheme for image generation or computer graphics - Not used for classification
architectural design, interior design - interior/garden/facade design, architectural layout plans
bandwidth reduction
bounding box - convex hull for polygons or 3D objects
cloth - animation, rendering or modeling of cloth/garment/textile, virtual dressing rooms
collision detection, intersection - intersection/collision detection of 3D objects
cropping - cropping of image borders
fluid dynamics - animation, rendering or modelling of fluid flows
force feedback - virtual force
image data format - conversion between different image or graphics formats
level of detail - level of detail, also for textures (e.g. mip-mapping)
medical - medical applications concerning e.g. heart, lung, brain, tumors
morphing - morphing or warping
parallel processing
particle system, point based geometry or rendering - rendering and animation of particle systems (e.g. fireworks, dust, clouds), point clouds, splatting
scene description - scene graphs, scene description languages, e.g. VRML
semi-transparency - screen-door effect, change of transparency values
weathering - weathering effects like e.g. aging, corrosion
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
2D
Two-dimensional
3D
Three-dimensional
4D
Four-dimensional, 3D in time
CAD
Computer-Aided Design (in computer graphics); Computer-Aided Detection (in image analysis)
MR
Magnetic Resonance (in image analysis); Mixed Reality (in computer graphics)
Stereo
Treatment of the images of exactly two cameras in a pairwise manner
Synonyms and Keywords

In patent documents the following abbreviations are often used:

ANN
Artificial Neural Network
AR
Augmented Reality
CT
Computed Tomography
DCE-MRI
Dynamic Contrast-Enhanced Magnetic Resonance Imaging
DCT
Discrete Cosine Transform
DRR
Digitally Reconstructed Radiograph
DTS
Digital Tomosynthesis
GUI
Graphical User Interface
IC
Integrated Circuit
ICP
Iterative Closest Point
LCD
Liquid Crystal Display
MRF
Markov Random Field
MRI
Magnetic Resonance Imaging
PCB
Printed Circuit Board
RGB
Red, Green, Blue
ROI
Region of Interest
SLAM
Simultaneous Localisation And Mapping
SNR
Signal-to-Noise Ratio
SPECT
Single Photon Emission Computed Tomography
US
Ultrasound
VOI
Volume of Interest
VR
Virtual Reality
General purpose image data processing
Definition statement
This subclass/group covers:

General purpose image data processing systems and methods.

Special rules of classification within this group

The IPC class G06T1/40 is not used. The corresponding documents are classified in G06T 1/20.

{Image acquisition}
Definition statement
This subclass/group covers:

Capturing or storing images from or to memory

References relevant to classification in this group
This subclass/group does not cover:
Scanning, transmission or reproduction of documents or the like
Television cameras
{Image feed-back for automatic industrial control, e.g. robot with camera ( robots B25J 19/023) }
Definition statement
This subclass/group covers:
  • Machine vision or tool control
  • Image feedback for robot navigation or walking
  • 3D vision systems.
References relevant to classification in this group
This subclass/group does not cover:
Accessories fitted to manipulators including video camera means
Vision controlled manipulators
Control of vehicles using a video camera
{Image watermarking}
Definition statement
This subclass/group covers:
  • Image watermarking in general.
  • Applications or software packages for watermarking.

Illustrative example - Hiding a digital image (message) into another digital image (carrier) (US6094483 - UNIV NEW YORK STATE RES FOUND):

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References relevant to classification in this group
This subclass/group does not cover:
Testing specially adapted to determine the identity or genuineness of paper currency or similar valuable papers
Audio watermarking
G10L19/00W
Arrangements for secret or secure communication using encryption of data
Arrangements for secret or secure communication using electronic signatures
Informative references
Attention is drawn to the following places, which may be of interest for search:
Security arrangements for protecting computers or computer systems against unauthorised activity
G06F21/00N
Circuits for prevention of unauthorised reproduction or copying
Scanning, transmission or reproduction of documents involving image watermarking
{Adaptive watermarking, e.g. Human Visual System (HVS)-based watermarking}
Definition statement
This subclass/group covers:
  • Adaptations based on Human Visual System [HVS].
  • Perceptual masking.
  • Preservation of image quality; Distortion minimization.
  • Methods to measure quality of watermarked images.
  • Measuring the balance between quality and robustness, i.e., fixed robustness, adapting quality, or vice versa.

Illustrative example - Changing a portion of an image based on an embedding strength map (EP1170938 - HITACHI LTD):

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{Output size adaptive watermarking}
Definition statement
This subclass/group covers:
  • Embedding without modifying the size of input.
  • Embedding or modifying the watermark directly in a coded image or video stream, without decoding first.
{Fragile watermarking, e.g. so as to detect tampering}
Definition statement
This subclass/group covers:
  • Birthday attacks.
  • Forgery.

Illustrative example - Changing pixels at selected positions according to a replacement table (WO2011021114 - NDS LIMITED):

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{Robust watermarking, e.g. average attack or collusion attack resistant}
Definition statement
This subclass/group covers:
  • Resistance; Resistance to attacks or distortions; Distortion compensation.
  • Strength.
  • Collusion attacks; Average attacks; Averaging.
  • Reliable detection, e.g. with reduced likelihood of false positive/negative.

Illustrative example - Watermarking an image using the difference of average intensity of two adjacent blocks (EP1927948 - FUJITSU LTD):

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{Compression invariant watermarking}
Definition statement
This subclass/group covers:

Watermarking techniques for JPEG or MPEG or for a wavelet transformed image.

Illustrative example - Embedded a watermark in a DC component region of a wavelet transformed image (US2004047489 - KOREA ELECTRONICS TELECOMM):

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{Geometric transfor invariant watermarking, e.g. affine transform invariant}
Definition statement
This subclass/group covers:
  • Robust against resizing or rotation or cropping, etc.
  • Determining the rescaling factor or rotation angle by using the watermarks so as to compensate the image, i.e. as a calibration signal.
  • Desynchronization attacks.

Illustrative example - Combining a reference mark with an identification mark and embedding them in image textures to detect the applied transformations (GB2378602 - CENTRAL RESEARCH LAB LTD):

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{using multiple or alternating watermarks}
Definition statement
This subclass/group covers:
  • Many, possibly different, watermarks on the same image, e.g. for copy or distribution control.
  • Same watermark repeated on different parts of the image.

Illustrative example - Encoding payload in relative positions and/or polarities of multiple embedded watermarks (WO0111563 - KONINKL PHILIPS ELECTRONICS NV):

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{using multiple thresholds}
Definition statement
This subclass/group covers:

Using thresholds to define ranges of detection probability or ranges of robustness.

Illustrative example - Multiple thresholds for reducing false detection likelihood

(EP1271401 - SONY UK LTD):

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{Time domain based watermarking, e.g. watermarks spread over several images}
Definition statement
This subclass/group covers:

Watermarks spread over several images or frames or a sequence.

Illustrative example - Alternating watermark patterns (e.g. by translation, mirror, rotation) to improve the reliability of scale factor measurement (WO2005109338 - KONINKL PHILIPS ELECTRONICS NV):

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{Payload characteristic determination in a watermarking scheme, e.g. number of bits to be embedded}
Definition statement
This subclass/group covers:

Illustrative example - Calculating capacity of DCT coefficients of a digital image file and selecting the ones apted to embedding, thereby providing robustness (US6724913 - HSU WEN-HSING):

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Processor architectures; Processor configuration, e.g. pipelining ( architectures of general purpose stored programme computers G06F 15/76)
Definition statement
This subclass/group covers:
  • Graphics accelerators; Graphic processing units (GPUs).
  • Parallel or massively parallel data bus specially adapted for image data processing.
  • Architecture or signal processor specially adapted for image data processing.
  • VLSI or SIMD or fine-grained machines specially adapted for image data processing.
  • Multiprocessor or multicomputer or multi-core specially adapted for image data processing.

Illustrative example - Ring architecture for image data processing (EP1495412 - DEERING MICHAEL F):

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References relevant to classification in this group
This subclass/group does not cover:
Architectures of general purpose stored programme computers
Arrangements for programme control, e.g. control unit
Memory management
Definition statement
This subclass/group covers:
  • Address generation or addressing circuit or BitBlt for image data processing.
  • 3D or virtual or cache memory specially adapted for image data processing.
  • Frame or screen or image memory specially adapted for image data processing.

Illustrative example - Cache memory for image processing (EP0589724 - QUANTEL LTD)

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References relevant to classification in this group
This subclass/group does not cover:
Accessing, addressing or allocating within memory systems or architectures
Ping-pong buffers
Digital stores characterised by the use of particular electric or magnetic storage elements
Arrangements for selecting an address in a digital store
Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
Definition statement
This subclass/group covers:

Geometric image transformations in the plane of the image.

References relevant to classification in this group
This subclass/group does not cover:
Matrix or vector computation
Geometric effects for 3D image rendering
Perspective computation for 3D image rendering
Geometric transformations for image enhancements
Conversion of standard for television systems
Informative references
Attention is drawn to the following places, which may be of interest for search:
Image animations
Geographic models
{Affine transformations (G06T 3/4038 , G06T 3/0068 take precedence ) }
Definition statement
This subclass/group covers:

Scaling and rotation.

References relevant to classification in this group
This subclass/group does not cover:
For image registration, e.g. elastic snapping
Demosaicing, e.g. colour filter array [CFA], Bayer pattern
{Context preserving transformation, e.g. by using an importance map (G06T 3/0062 takes precedence ) }
Definition statement
This subclass/group covers:
  • Selective warping according to an importance map; Smart image reduction.
  • Seam carving; Liquid resizing; Image retargeting.

Illustrative example - Seam carving (EP1968008 - MITSUBISHI ELECTRIC CORP):

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References relevant to classification in this group
This subclass/group does not cover:
Panospheric to cylindrical image transformation
{Fisheye, wide-angle transformation}
Definition statement
This subclass/group covers:

Establishing a lens for a region-of-interest.

Illustrative example - Variable magnification of part of the image (FR2828571 - SAGEM SA):

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{Detail-in-context presentation (G06T 3/0018 takes precedence ) }
Definition statement
This subclass/group covers:
  • Side or corner panels; Perspective wall.
  • Document lens.

Illustrative example - Corner / side panels (EP0651350 - XEROX CORP):

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References relevant to classification in this group
This subclass/group does not cover:
Fisheye, wide-angle transformation
{for topological mapping of a higher dimensional structure on a lower dimensional surface}
Definition statement
This subclass/group covers:

Flattening the scanned image of a bound book.

Illustrative example - Bound book flattening (FR2832242 - I2S):

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References relevant to classification in this group
This subclass/group does not cover:
Panospheric to cylindrical image transformation
Texture mapping
Manipulating 3D models or images for computer graphics
Special rules of classification within this group

The boundaries between G06T 3/0031 and subgroups on the one hand, and G06T 15/00 (in particular G06T 15/08 and G06T 15/10) and G06T 19/00 on the other is not yet completely determined. Thus double classification should be considered.

{Reshaping or unfolding a 3D tree structure onto a 2D plane}
Definition statement
This subclass/group covers:

Curved planar reformation [CPR]).

Informative references
Attention is drawn to the following places, which may be of interest for search:
Manipulating 3D models or images for computer graphics
{Surface of revolution to planar image transformation}
Definition statement
This subclass/group covers:

Mapping a surface of revolution to a plane, e.g. mapping a pot or a can to a plane.

Illustrative example - Pre-processing for compensating the label deformation due to the form of the container (FR2870028 - KALLISTO SARL):

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{for projecting an image on a non-planar surface, e.g. a geodetic screen}
Definition statement
This subclass/group covers:
  • Geometric image transformation for projecting an image on a multi-projectors system or on a geodetic screen; Dome imaging.
  • Geometric image transformation for projecting an image through multi-planar displays.
References relevant to classification in this group
This subclass/group does not cover:
Texture mapping
Special rules of classification within this group

The boundaries between G06T 3/005 on the one hand, and G06T 15/10 and G06T 19/00 on the other is not yet completely determined. Thus double classification should be considered.

{the transformation method being selected according to the characteristics of the input image}
Definition statement
This subclass/group covers:
  • Selecting the interpolation method depending on the scale factor.
  • Selecting the interpolation method depending on media type or image appearance characteristics.

Illustrative example - Various stored interpolations such as cubic convolution, linear and replication can be selected to suit differing types of images (WO9016035 - EASTMAN KODAK CO):

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{Panospheric to cylindrical image transformation}
Definition statement
This subclass/group covers:
  • Omnidirectional or hyperboloidal to cylindrical image transformation or mapping; Catadioptric transformation, e.g. images from surveillance cameras.
  • Panospheric image transformation or mapping by using the output of a multiple cameras system.

Illustrative example - Transforming a panospheric image obtained using a convex mirror (WO9750252 - BEHERE CORP):

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{for image registration, e.g. elastic snapping}
Definition statement
This subclass/group covers:

Geometric image transformation for

  • Iterative image registration.
  • Spline-based image registration.
  • Mutual-information-based registration.
  • Phase correlation or FFT-based methods.
  • Using fiducial points, e.g. landmarks.
  • Maximized mutual information-based methods.
References relevant to classification in this group
This subclass/group does not cover:
Determining the parameters for the image registration
{by elastic snapping}
Definition statement
This subclass/group covers:
  • Elastic mapping or snapping or matching; Deformable mapping.
  • Diffeomorphic representations of deformations in order to control the image registration process.

Illustrative example - Elastic snap (FR2717926 - HITACHI SOFTWARE ENG):

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{Spatio-temporal transformations, e.g. video cubism}
Definition statement
This subclass/group covers:
  • Video cubism; Video cube.
  • Dynamic panoramic video.
  • Stylized video cubes.
{for image warping, i.e. transforming by individually repositioning each pixel}
Informative references
Attention is drawn to the following places, which may be of interest for search:
Image animation
Scaling the whole image or part thereof
Definition statement
This subclass/group covers:
  • Resampling; Resolution conversion.
  • Zooming or expanding or magnifying or enlarging or upscaling.
  • Shrinking or reducing or compressing or downscaling.
  • Pyramidal partitions; Storing sub-sampled copies.
  • Area based or weighted interpolation; Scaling by surface fitting, e.g. piecewise polynomial surfaces or B-splines or Beta-splines.
  • Two-steps image scaling, e.g. by stretching.
References relevant to classification in this group
This subclass/group does not cover:
Polynomial surface description for image modeling
Scanning, transmission or reproduction of documents involving modification of image resolution.
Studio circuits for television systems involving alteration of picture size or orientation
Frame rate conversion; de-interlacing
{Interpolation-based scaling, e.g. bilinear interpolation (G06T 3/4015 , G06T 3/403 take precedence ) }
Definition statement
This subclass/group covers:
  • Linear or bi-linear or tetrahedral or cubic image interpolation.
  • Adaptive interpolation, e.g. the coefficients of the interpolation depend on the pattern of the local structure.

Illustrative example - Third order spline interpolation (EP1089226 - FUJI PHOTO FILM CO LTD):

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References relevant to classification in this group
This subclass/group does not cover:
Demosaicing, e.g. colour filter array [CFA], Bayer pattern
Edge-driven scaling
{Demosaicing, e.g. colour filter array [CFA} , Bayer pattern]
Definition statement
This subclass/group covers:
  • CFA demosaicing or demosaicking or interpolating.
  • Bayer pattern.
  • Colour-separated images, i.e. one colour in each image quadrant.

Illustrative examples - Image demosaicing (EP1389771 - AGILENT TECHNOLOGIES INC):

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  • Colour-separated image (EP1874034 - SAMSUNG ELECTRO MECH):

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{Decimation- or insertion-based scaling, e.g. pixel or line decimation}
Definition statement
This subclass/group covers:
  • Pixel or row deletion or removal.
  • Pixel or row insertion or duplication or replication.
  • Decimating FIR filters.
  • Array indexes or tables, e.g. LUT.

Illustrative example - Decimating by using two array of indexes (EP1351189 - ERICSSON TELEFON AB L M):

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{Edge-driven scaling}
Definition statement
This subclass/group covers:
  • Edge adaptive or directed or dependent or following or preserving interpolation; Edge preservation.
  • Edge map injecting or projecting or combining or superimposing.

Illustrative example - Correcting for abnormalities next to boundaries (EP1018705 - HEWLETT PACKARD CO):

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{for image mosaicing, i.e. plane images composed of plane sub-images}
Definition statement
This subclass/group covers:
  • Image mosaicing or mosaiking.
  • Panorama views.
  • Mosaic of video sequences; Salient video still; Video collage or synopsis.

Illustrative example - Image mosaicing for microscopy applications (EP1016031 - BACUS RES LAB INC):

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Informative references
Attention is drawn to the following places, which may be of interest for search:
Image processing arrangements associated with discharge tubes with provision for introducing objects or material to be exposed to the discharge
{using neural networks}
Definition statement
This subclass/group covers:
  • Using neural networks specially adapted for image interpolation.
  • Using neural networks specially adapted for interpolation coefficient selection.

Illustrative example - Using a neural network to select the coefficients of a polynomial interpolation (EP1321896 - IBM):

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References relevant to classification in this group
This subclass/group does not cover:
Computer systems using neural network models.
{Super resolution, i.e. output image resolution higher than sensor resolution}
Definition statement
This subclass/group covers:
  • Super resolution by fitting the pixel intensity to a mathematical function.
  • Super resolution from image sequences; Images or frames addition or coaddition or combination.
  • Super resolution by iteratively applying constraints, e.g. energy reduction, on the transform domain and inverse transforming.

Illustrative example - fitting a mathematical function and resampling (EP0696017 - HEWLETT PACKARD CO):

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References relevant to classification in this group
This subclass/group does not cover:
Image enhancement by the use of more than one image, e.g. by averaging or subtraction.
{by injecting details from a different spectral band}
Definition statement
This subclass/group covers:

Multisensor or multiband images fusion.

{by subpixel displacement}
Definition statement
This subclass/group covers:

Illustrative example of subject matter covered in this group - Displaying sub-frames at spatially offset positions (US2005168494 - HEWLETT PACKARD DEVELOPMENT CO):

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{by iteratively correcting the provisional high resolution image using the original low-resolution image}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group - Iterative correction of the high-resolution image (EP1018705 - HEWLETT PACKARD CO):

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{Transform-based scaling, e.g. FFT domain scaling}
Definition statement
This subclass/group covers:
  • DCT coefficients decimation or insertion for image scaling.
  • Zero padding DCT coefficients for image scaling.
  • Downscaling by selecting a specific Wavelet subband.

Illustrative example - Enlargement / reduction through DCT interpolation / decimation (WO9515538 - POLAROID CORP):

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{Image resolution transcoding, e.g. client/server architecture}
Definition statement
This subclass/group covers:

Adapting the image resolution to the client's capabilities.

Illustrative example - The processing unit is coupled downstream from video cross-point switcher for generating additionally scaled video streams by additional video scaling on initially scaled video stream (WO2009126683 - HARRIS CORP):

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Informative references
Attention is drawn to the following places, which may be of interest for search:
Server components or server architectures for processing of video elementary streams by altering the spatial resolution.
Rotation of a whole image or part thereof
Definition statement
This subclass/group covers:
  • Transpose or continuous write-transpose-read.
  • Mirror.
  • Rung-length (RL) rotation.
Informative references
Attention is drawn to the following places, which may be of interest for search:
Scanning, transmission or reproduction of documents involving image rotation.
Studio circuits for television systems involving alteration of picture size or orientation.
{Block rotation, e.g. by recursive reversing or rotating}
Definition statement
This subclass/group covers:

Illustrative example - Rotation by recursive reversing (EP0744711 - CANON KK):

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{Rotation by memory addressing or mapping}
Definition statement
This subclass/group covers:

Illustrative example - Continuous read-transpose-write (EP0497493 - AMERICAN TELEPHONE & TELEGRAPH):

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{Skewing or deskewing, e.g. by two-pass or three-pass rotation}
Definition statement
This subclass/group covers:
  • Shift processing
  • Rotation by shearing.

Illustrative example - Image rotation by two-pass de-skewing (EP0978802 - KONISHIROKU PHOTO IND):

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Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
Definition statement
This subclass/group covers:

Image enhancement or restoration using:

  • Denoising, smoothing
  • Deblurring, sharpening, unsharp masking
  • Retouching, inpainting, scratch removal
  • Geometric correction
  • Non-spatial domain filtering
  • Use of local operators
  • Morphological operators for image enhancement
  • Histogram techniques
  • Techniques involving the use of more than one image, e.g. averaging, subtraction
Relationship between large subject matter areas

G06T is the function place for image data processing or generation. Image data processing or generation specially adapted for a particular application is classified in the relevant subclass, e.g. G06K 9/00, H04N

References relevant to classification in this group
This subclass/group does not cover:
Image processing adapted to be used in scanners, printers, photocopying machines, displays or similar devices, including colour space conversion, colour space processing, halftoning or halftone screening
Image processing exclusively adapted to be used in an image pickup device containing an electronic image sensor [EIS] or in studio devices or equipment
Informative references
Attention is drawn to the following places, which may be of interest for search:
Image preprocessing for pattern recognition
Neural networks in general
Multi-scale pyramids for image enhancement (documents classified before 2005)
Neural networks [ANN], fuzzy logic, genetic algorithms, artificial intelligence [AI], e.g. expert systems for image enhancement (documents classified before 2005)
Special rules of classification within this group

This group focuses on image processing algorithms. Although such algorithms sometimes need to take into account characteristics of the underlying image acquisition apparatus, inventions to the image acquisition apparatus per se are outside the scope of this group.

Whenever possible, additional information should be classified using one or more of the Indexing Codes from the ranges of G06T 2200/00(see FCR document re. G06T) or G06T 2207/00 (see FCR document re. G06T 2207/00).

If a document contains considerable contribution within the scope of another group, the document should be forwarded to this group for classification. In particular, the groups mentioned under "Informative References" in G06T 5/00 or one of its subgroups should be considered for circulation.

The classification symbol G06T 5/00 should be allocated to documents concerning:

Interactive / multiple choice image processing, e.g. choosing outputs from multiple enhancement algorithms

Other image enhancement out of the scope of the subgroups

Illustrative examples:

Fig. 6 from US5553159 A (applicant Fuji Photo Film Co Ltd)

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Fig. 4 from US2005265633 A1 (applicant Sarnoff Corp.):

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Synonyms and Keywords

In patent documents the following abbreviations are often used:

HDR
High Dynamic Range (Imaging)
HDRI
High Dynamic Range Imaging
HMM
Hidden Markov Model
PSF
Point Spread Function
{Image restoration}
Definition statement
This subclass/group covers:
  • Image restoration based on properties or models of the human vision system [HVS]

Illustrative examples:

Fig. 4a from EP1322113 A1 (applicant Sharp KK):

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Fig. 2 from US2010265404 A1 (applicant General Instrument Corporation):

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Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/001 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Denoising; Smoothing ( noise processing or correction adapted to be used in an image pickup device containing and electronic image sensor H04N 5/217 , H04N 5/357 to H04N 5/365) }
Definition statement
This subclass/group covers:
  • Removing noise from images
  • Temporal denoising, spatio-temporal noise filtering: add the Indexing Code G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
  • Removing pattern noise from images
  • Image smoothing
  • Image blurring, adding motion blur to images, adding blur to images
  • Edge-adaptive smoothing: add the Indexing Code G06T 2207/20192 Edge enhancement; Edge preservation
  • Smoothing of depth map in stereo or range images
  • Antialiasing by image filtering
  • Denoising or smoothing using singular value decomposition [SVD]

Illustrative example: Fig. 3A and 3B from WO2012000800 A1 (applicant DIGITALOPTICS CORPORATION EUROPE LIMITED):

media40.png

References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

Noise processing or defect pixel recognition and correction adapted to be used in an image pickup device containing an electronic image sensor [EIS], e.g. fixed pattern noise of image sensors
Informative references
Attention is drawn to the following places, which may be of interest for search:
Antialiasing during drawing of lines
Antialiasing during rasterisation of images
Noise filtering, if essentially linked to pattern recognition
Noise or error suppression in colour picture communication systems
Temporal denoising / smoothing to reduce eye strain or fatigue in stereo vision
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/002 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Deblurring; Sharpening ( vibration or motion blur correction for cameras comprising an electronic image sensor H04N 5/23264) }
Definition statement
This subclass/group covers:
  • Deblurring
  • Removing motion blur from images: add the Indexing Code G06T 2207/20201 Motion blur correction
  • Point-spread function [PSF] model of blurring
  • Deconvolution
  • Modulation transfer function [MTF]
  • Sharpening, crispening
  • Edge enhancement, edge boosting: add the Indexing Code G06T 2207/20192 Edge enhancement; Edge preservation

Illustrative examples: Fig. 4B from US2009110303 A1 (applicant Toshiba KK):

media41.png

Fig. 1 from US2010246989 A1 (inventors Agrawal et al.):

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References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

Motion blur removal adapted to be used in an image pickup device containing an electronic image sensor [EIS]
Informative references
Attention is drawn to the following places, which may be of interest for search:
Edge-adaptive scaling
Edge or detail enhancement for scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission
Edge or detail enhancement in colour picture communication systems
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/003 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Unsharp masking}
Definition statement
This subclass/group covers:
  • Unsharp masking
  • Adding or subtracting a processed version of an image to or from the image

Illustrative example - Fig. 27A from WO2008101129 A1 (applicant Luminex Technologies Corp.):

media43.png

Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/004 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Retouching; Inpainting; Scratch removal ( detecting, correction, reducing or removing defects, e.g. non-responsive pixels of solid state image sensors H04N 5/367 , scratch removal for cinematographic films scanned by electronic image sensor H04N 5/253) }
Definition statement
This subclass/group covers:
  • Concealing defective pixels in images
  • Scratch removal
  • Inpainting by image filtering or by replacing patches within an image using a generated image or texture patch, or a patch retrieved from another source, e.g. image database, internet, etc.
  • Correcting redeye defects: add the Indexing Code G06T 2207/30216: Redeye defect

Illustrative examples: Fig. 6 from US2008080752 A1 (applicant Harris Corp.):

media44.png

Relationship between large subject matter areas
Scratch removal adapted to be used in scanners, printers, photocopying machines, displays or similar devices
References relevant to classification in this group
This subclass/group does not cover:
Scratch removal of image signals generated by scanning cinematographic films
Detecting and concealing of defect pixel adapted to be used in or for an image pickup device containing an electronic image sensor
Informative references
Attention is drawn to the following places, which may be of interest for search:
Finding redeye defects
Texture generation as such
Recognising eye features
Retouching monochrome or colour images adapted to be used in scanners, printers, photocopying machines, displays or similar devices
Redeye correction adapted to be used in scanners, printers, photocopying machines, displays or similar devices
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/005 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Geometric correction ( detecting, correcting, reducing or removing artefacts resulting only from the lens unit, e.g. flare, shading, vignetting or "cos4" H04N 5/3572 , correction of chromatic aberrations adapted to be used in an image pickup device containing and electronic image sensor H04N 9/045) }
Definition statement
This subclass/group covers:
  • Correcting lens distortions or aberrations
  • Correcting pin-cushion, barrel, trapezoidal or fish-eye distortions
  • Calibrating parameters of lens distortion
  • Reference grids, coordinate mapping

Illustrative example:

media45.png

References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

Correction of lens distortions or aberrations, pin cushion, barrel, trapezoidal or fish-eye distortions adapted to be used in or for an image pickup device containing an electronic image sensor
Informative references
Attention is drawn to the following places, which may be of interest for search:
Details of image transformations for geometric correction
Camera calibration (intrinsic and extrinsic parameters)
Normalisation of the pattern dimension for improving pattern recognition
Correction of chromatic aberrations adapted to be used in an image pickup device containing an electronic image sensor [EIS]
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/006 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Dynamic range modification ( applied in cameras using an electronic image sensor H04N 5/2355 , H04N 5/2356) }
Definition statement
This subclass/group covers:

Contrast enhancement based on a combination of local and global properties

Illustrative examples: Fig. 3 from US2010201883 A1 (applicant Xilinx Inc.):

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Fig. 1 from US2011096988 A1 (applicant Himax Media Solutions Inc.):

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References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

HDR imaging and HDR processing adapted to be used in an image pickup device containing an electronic image sensor [EIS], e.g. dynamic range increase, bracketing, use of image signal histograms or brightness compensation by controlling shutter, filter, gain, etc.
Informative references
Attention is drawn to the following places, which may be of interest for search:
Equalising stereo images or image sequences
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/007 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Local, e.g. shadow enhancement}
Definition statement
This subclass/group covers:
  • Local contrast enhancement, e.g. locally adaptive filtering
  • Retinex processing

Illustrative examples: Fig. 2 from WO2006108299 A1 (applicant ACD Systems Ltd.):

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Fig. 1 from US6788822 B1 (applicant Sharp KK):

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Informative references
Attention is drawn to the following places, which may be of interest for search:
Unsharp masking
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/008 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

{Global, i.e. based on properties of the image as a whole ( applied in cameras using an electronic image sensor H04N 5/23229 , H04N 5/235) }
Definition statement
This subclass/group covers:
  • Global contrast enhancement or tone mapping to increase the dynamic range of an image, based on properties of the whole image, e.g. global statistics or histograms
  • Contrast stretching, brightness equalisation
  • Gamma and gradation correction in general
  • Tone mapping for high dynamic range [HDR] imaging: add the Indexing Code G06T 2207/20208 High dynamic range [HDR] image processing
  • Intensity mapping, e.g. using lookup tables [LUT]

Illustrative example: Fig. 4 from US2010309216 A1 (applicant Panasonic Corporation):

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References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

Picture signal circuitry for controlling amplitude response in television systems
Gamma control in television systems
HDR imaging and HDR processing adapted to be used in an image pickup device containing an electronic image sensor [EIS], e.g. dynamic range increase, bracketing, use of image signal histograms or brightness compensation by controlling shutter, filter, gain, etc.
Special rules of classification within this group

Whenever possible or appropriate, documents classified in the subgroup of G06T 5/009 should additionally be assigned ECLA symbols from the range G06T 5/10 to G06T 5/50.

by non-spatial domain filtering { ( applied in cameras using an electronic image sensor H04N 5/23229 , H04N 5/235 , H04N 5/253 , H04N 5/367) }
Definition statement
This subclass/group covers:

All transform domain-based enhancement methods, e.g. using:

Fourier transform, Discrete Fourier transform [DFT] or Fast Fourier transform [FFT]: add the Indexing Code G06T 2207/20056 Discrete and fast Fourier transform, [DFT, FFT]

Hadamard transform

Discrete cosine transform [DCT]: add the Indexing Code G06T 2207/20052 Discrete cosine transform [DCT]

Wavelet transform, Discrete Wavelet transform [DWT]: add the Indexing Code G06T 2207/20064 Wavelet transform [DWT]

Illustrative example - Fig. 1 from US2010111436 A1 (applicant Samsung Techwin Co. Ltd.):

media51.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Hierarchical image enhancement
Image restoration
by the use of local operators { ( applied in cameras using an electronic image sensor H04N 5/23229 , H04N 5/235 , H04N 5/253 , H04N 5/367) }
Definition statement
This subclass/group covers:
  • Convolution with a mask or kernel in the spatial domain
  • High-pass filter, low-pass filter
  • Gauss filter, Laplace filter
  • Averaging filter, mean filter, blurring filter
  • Differential filters (e.g. Sobel operator)
  • Median filter: add the Indexing Code G06T 2207/20032 Median filtering
  • Bilateral filter: add the Indexing Code G06T 2207/20028 Bilateral filtering
  • Minimum, maximum or and rank filtering
  • Wiener filter
  • Phase-locked loops, detectors, mixers
  • Recursive filter
  • Distance transforms
  • Local image processing architectures

Illustrative example: Fig. 2a from US6430321 B1 (applicant Hewlett Packard Co.):

media52.png

References relevant to classification in this group
This subclass/group does not cover:
Scratch removal of image signals generated by scanning cinematographic films
Detecting and concealing of defect pixel adapted to be used in or for an image pickup device containing an electronic image sensor

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

Further processing of the captured image without influencing the image pickup process in an image pickup device containing an electronic image sensor
Informative references
Attention is drawn to the following places, which may be of interest for search:
Local operators for determining features used in pattern recognition
Erosion or dilatation, e.g. thinning
Definition statement
This subclass/group covers:

All morphology-based operations for image enhancement, e.g.:

  • Thickening, thinning
  • Opening, closing
  • Erosion, dilation
  • Structuring elements
  • Skeletons
  • Geodesic transforms

Illustrative examples: Fig. 1 from US2010040263 A1 (applicant STI Medical Systems LLC)

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Fig. 15 from US5204752 A (applicant Ricoh KK)

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Informative references
Attention is drawn to the following places, which may be of interest for search:
Morphological operations for segmentation
Thinning of patterns in pattern recognition
by the use of histogram techniques { ( applied in cameras using an electronic image sensor H04N 5/23229 , H04N 5/235) }
Definition statement
This subclass/group covers:

All histogram-based image enhancement methods

Illustrative example: Fig. 3A and 3B from EP2267655 A2 (applicant Canon KK):

media55.png

References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

HDR imaging and HDR processing adapted to be used in an image pickup device containing an electronic image sensor [EIS], e.g. dynamic range increase, bracketing, use of image signal histograms or brightness compensation by controlling shutter, filter, gain, etc.
Informative references
Attention is drawn to the following places, which may be of interest for search:
Dynamic range modification
Histogram techniques adapted to be used in scanners, printers, photocopying machines, displays or similar devices
Equalising stereoscopic images or image sequences
by the use of more than one image, e.g. averaging, subtraction { ( applied in cameras using an electronic image sensor H04N 5/23229 , H04N 5/235) }
Definition statement
This subclass/group covers:

Image averaging (add the Indexing Code G06T 2207/20216)

Image fusion, image merging: (add the Indexing Code G06T 2207/20221)

Image subtraction: add the Indexing Code G06T 2207/20224

Enhanced final image by combining multiple, e.g. degraded, images, while maintaining the same number of pixels (for increased number of pixels: see G06T 3/40)

Full-field focus from multiple of depth-of-field images, e.g. from confocal microscopy

Processing of Synthetic Aperture Radar [SAR] images

Energy subtraction

Bright field, dark field processing

Angiography image processing

High dynamic range [HDR] image processing (add the Indexing Code G06T 2207/20208)

Multispectral image processing

Computational photography, e.g. coded aperture imaging (add the Indexing Code G06T 2200/21)

Illustrative example: Fig. 1 from EP2199975 A1 (applicant Samsung Electronics Co. Ltd.):

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References relevant to classification in this group
This subclass/group does not cover:

Examples of places where the subject matter of this group is covered when specially adapted, used for a particular purpose, or incorporated in a larger system:

Further processing of the captured image without influencing the image pickup process in an image pickup device containing an electronic image sensor
HDR imaging and HDR processing adapted to be used in an image pickup device containing an electronic image sensor [EIS], e.g. dynamic range increase, bracketing, use of image signal histograms or brightness compensation by controlling shutter, filter, gain, etc.
Informative references
Attention is drawn to the following places, which may be of interest for search:
Super-resolution techniques
Unsharp masking
Synthetic Aperture Radar [SAR] processing, if focus is not on the image processing
Compounding in ultrasound imaging (relating to noise removal from several ultrasound images)
Confocal scanning microscopes
Image analysis, e.g. from bit-mapped to non bit-mapped
Definition statement
This subclass/group covers:
  • Inspection-detection on images, e.g. flaw detection; Industrial image inspection using e.g. a design-rule based approach or an image reference. Industrial image inspection checking presence / absence; Biomedical image inspection.
  • Camera calibration, e.g. determining intrinsic or extrinsic parameters; Calibration of stereo cameras, e.g. determining the transformation between left and right camera coordinate systems.
  • Determining parameters from multiple pictures, e.g. registration / alignment of images, for instance by correlation-, feature- or transform domain-based approaches.
  • Determining the position or orientation of objects.
  • Depth or shape recovery from shading, specularities, texture, perspective effects, e.g. vanishing points, or line drawings; Depth or shape recovery from multiple images involving amongst others contours, focus, motion, multiple light sources, photometric stereo or stereo images.
  • Segmentation or edge detection, e.g. involving probabilistic or graph-based approaches, deformable models, morphological operators, transform domain-based approaches or the use of more than two images.
  • Motion-based segmentation.
  • Analysis of motion, tracking or change detection, e.g. by block matching, feature-based methods, gradient-based methods, hierarchical or stochastic approaches, motion estimation from a sequence of stereo images.
  • Texture analysis, e.g. based on statistical or structural descriptions.
  • Colour analysis.
  • Analysis of geometric attributes, e.g. area, perimeter, diameter, volume, convexity, concavity, centre of gravity, moments or symmetry.
Relationship between large subject matter areas

G06T is the function place for image data processing or generation. Image data processing or generation specially adapted for a particular application is classified in the relevant subclass, e.g. G06K 9/00, H04N

References relevant to classification in this group
This subclass/group does not cover:
Processing seismic data
Bioinformatics
G06F19/00C
Medical informatics
Special rules of classification within this group

This group focuses on image processing algorithms. Although such algorithms sometimes need to take into account characteristics of the underlying image acquisition apparatus, inventions to the image acquisition apparatus per se are outside the scope of this group.

Whenever possible, additional information should be classified using one or more of the Indexing Codes from the ranges of G06T 2200/00(see FCR document re. G06T) or G06T 2207/00(see FCR document re. G06T 2207/00).

If a document contains considerable contribution within the scope of another group, the document should be considered for classification in this group. In particular, the groups mentioned under "Informative References" in G06T 7/00 or one of its subgroups should be considered.

The classification symbol G06T 7/00 is allocated to documents concerning:

  • Architectures of image analysis systems, see G06T 1/20 for processor architectures
  • MPEG7 descriptors, if not provided for elsewhere
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
CAD
Computer-Aided Detection
Stereo
Treatment of the images of exactly two cameras in a pairwise manner
Synonyms and Keywords

In documents the following abbreviations are often used:

AAM
Active appearance model
ASM
Active shape model
HMM
Hidden Markov Model
LBP
Local Binary Pattern
LPE
ligne de partage des eaux (French expression for watershed segmentation)
RANSAC
Random Sampling (and) Consensus
{Inspection of images, e.g. flaw detection (G06T 7/004 takes precedence ) }
Definition statement
This subclass/group covers:
  • Quality, conformity control
  • Defects, abnormality, incompleteness
  • Acceptability determination
  • User interface for automated visual inspection
  • Database-to-object inspection
References relevant to classification in this group
This subclass/group does not cover:
Determining position or orientation of objects
Special rules of classification within this group

This subgroup is an application-oriented group. Therefore, documents classified herein should also be classified in a function-oriented group, if they contain a considerable contribution on the respective function.

For documents classified herein, it is mandatory to also assign the appropriate Indexing Codes from the G06T 2200/00 and G06T 2207/00 ranges.

The classification symbol G06T 7/0002 is allocated to documents concerning image testing, image quality inspection: add the Indexing Code G06T 2207/30168 (Image quality inspection)

{Industrial image inspection}
Definition statement
This subclass/group covers:
  • Quality, conformity control in industrial context (add an Indexing Code from the Indexing Code range of G06T 2207/30108 to G06T 2207/30164: Industrial image inspection)
  • Defects, abnormality in industrial context
  • Acceptability determination in industrial context
  • User interfaces for automated visual inspection in industrial context (add the Indexing Code G06T 2200/24: involving graphical user interfaces [GUIs])
  • "Teaching" (macros for inspection algorithms)
  • Database-to-object inspection in industrial context
  • Printing quality (add the Indexing Code G06T 2207/30144: Printing quality)
Informative references
Attention is drawn to the following places, which may be of interest for search:
Investigating the presence of flaws or contamination on materials
Contactless testing using optical radiation for printed circuits
Contactless testing using optical radiation for individual semiconductor devices
Photolithography mask inspection
G03F7/20T22
Monitoring wafer production
H01L21/66
Component placement (in PCB manufacturing)
{using a design-rule based approach}
Definition statement
This subclass/group covers:

Verifying geometric design rules or known geometric parameters, e.g. width or spacing of structures, repetitive patterns

Illustrative examples: L. Onural and S. H. Oguz: "An Automated System for Design-Rule-Based Visual Inspection of Printed Circuit Boards", Proceedings of the International Conference on Robotics and Automation", April 9 - 11, 1991, Sacramento, IEEE Comp. Soc. Press, vol. 7, pp. 2696 - 2701

from US2009039263 A1 (applicant Fuji Photo Film Co. Ltd.):

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{checking presence/absence}
Definition statement
This subclass/group covers:
  • Detecting the absence of an item that should be there
  • Detecting incompleteness

Illustrative examples: WO2007010473, WO2009029051.

From WO2010017533 A2 (applicant Stephen Glickman et al.):

media58.png

{using an image reference approach ( image matching for pattern recognition or image matching in general G06K9/64A2) }
Definition statement
This subclass/group covers:
  • Comparison to a reference image, standard image, ground truth image, gold standard
  • Reference image taken by a camera or determined from computer-aided design data

Illustrative examples: WO03081531.

From US2011102573 A1 (applicant T. Honda et al.):

media59.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Image matching for pattern recognition or image matching in general
G06K9/64A2
{Biomedical image inspection}
Definition statement
This subclass/group covers:

Defects, abnormality in biomedical context: add an Indexing Code from the range of G06T 2207/30004 to G06T 2207/30104 Biomedical image processing

Computer-aided detection [CAD]

Detecting, measuring, scoring, grading of

  • Disease, pathology, lesions
  • Cancer, tumor, tumour, malignancy, nodule
  • Emphysema
  • Microcalcifications
  • Polyps
  • Scar, non-viable tissue
  • Osteoporosis, fracture risk prediction, Arthritis
  • Alzheimer disease
  • Scoring wrinkles, ageing
  • Tissue abnormalities in microscopic images, e.g. inflammation, deformations
  • Grading of living plants

Illustrative examples:

Fig. 1 from US2010271470 A1 (applicant LVMH Recherche)

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Fig. 9 from US2009141955 A1 (applicant Fuji Film Co. Ltd.)

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from WO03073946 A1 (applicant Eurosurgical)

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Informative references
Attention is drawn to the following places, which may be of interest for search:
Apparatus for radiation diagnostics
Diagnosis using ultrasound
MR imaging
Ultrasound imaging
Bioinformatics
G06F19/00C
Medical informatics
Recognising microscopic objects
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Biomedical
biological or medical
{using an image reference approach ( image matching for pattern recognition or image matching in general G06K9/64A2) }
Definition statement
This subclass/group covers:
  • Comparison to a reference image, standard image, atlas...
  • Reference image taken from different patient or patients, or reference image taken from spatially different anatomical regions of the same patient, e.g. comparison of left and right body parts.

Illustrative examples

  • WO2005023086 A2, WO0243003 A1
  • Fig. 17 from WO2007058632 A1 (applicant Agency Science Tech & Res. et al.):

media63.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Image matching for pattern recognition or image matching in general
G06K9/64A2
{involving temporal comparison ( change detection in general G06T 7/20) }
Definition statement
This subclass/group covers:
  • Follow-up studies, comparison of images from different points of time, temporal difference images, temporal subtraction images, biomedical change detection.
  • Reference image taken from the same patient and the same anatomical region.
  • Subtraction angiography for abnormality detection.
  • Assessment of dynamic contrast enhancement, wash-in/wash-out for abnormality detection.

Illustrative examples:

  • US2004081342 A1, US2001002934 A1, US6063030 A
  • Fig. 5 from EP1956552 A1 (applicant Agfa Gevaert):

media64.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Change detection in general
Image matching for pattern recognition or image matching in general
G06K9/64A2
{Camera calibration, e.g. determining intrinsic or extrinsic parameters}
Definition statement
This subclass/group covers:

Geometric camera calibration

Illustrative example from EP2202686 A1 (applicant Huawei Device Co. Ltd.):

media65.png

References relevant to classification in this group
This subclass/group does not cover:
Calibration patterns
Autofocus
White balance, colour cast correction
Correction of chromatic aberrations adapted to be used in an image pickup device containing an electronic image sensor
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geometric correction of lens distortion
Camera pose without calibration context
{Stereo camera calibration, e.g. determination of the transformation between left camera coordinate system and right camera coordinate system ( calibration aspects for stereoscopic image generation H04N13/00S2A7) }
Definition statement
This subclass/group covers:

Illustrative example: Fig. 4 from US2006078197 A1 (applicant Omron Tateisi Electronics Co.):

media66.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Calibration aspects for stereoscopic image generation
{Determining parameters from multiple pictures ( depth or shape from stereo images G06T 7/0075 ; depth or shape from multiple images G06T 7/0065 ; stereo camera calibration G06T 7/002) }
References relevant to classification in this group
This subclass/group does not cover:
Industrial image inspection using an image reference approach
Biomedical image inspection using an image reference approach
Stereo camera calibration
Depth map creation
Segmentation involving the use of two or more images
Computing motion from a sequence of stereo images
Image-based rendering
3D from 2D images with intermediate modelling
Special rules of classification within this group

The classification symbol G06T 7/0022 is allocated to documents concerning:

  • Disparity, correspondence, stereopsis, if not provided for elsewhere
  • Disparity calculation for the production of 3D images from 2D images without intermediate modelling: add the Indexing Code G06T 2207/20228 (Disparity calculation for image-based rendering)
{Registration of images, e.g. alignment of images ( image matching for pattern recognition or image matching in general G06K9/64A2) }
Definition statement
This subclass/group covers:
  • Registration means determining the alignment of images or finding their relative position. Determining the registration transformation parameters.
  • Registration of image subparts for the construction of mosaics image (add the Indexing Code G06T 2200/32: involving image mosaicing)
  • Multi-modal, cross-modal, across-modal registration of medical image data sets (add an Indexing Code from the range of G06T 2207/30004 to G06T 2207/30104: Biomedical image processing)
  • Registration with medical atlas (add an Indexing Code from the range of G06T 2207/30004 to G06T 2207/30104: Biomedical image processing)
  • Registration of pre-operative and intra-operative medical image data sets (add an Indexing Code from the range of G06T 2207/30004 to G06T 2207/30104: Biomedical image processing)
  • Registration for change detection in biomedical or remote sensing images (change detection see also G06T 7/20)
  • Registration of models
  • Registration of a model with an image
  • Registration of range data, point clouds (ICP algorithm)
  • 2D/2D, 2D/3D, 3D/3D registration
  • Interactive registration (add an Indexing Code from the range of G06T 2207/20092 to G06T 2207/20108: Interactive image processing based on input by user)
References relevant to classification in this group
This subclass/group does not cover:
Registration of a model with an image, if for segmentation
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geometric transformation of the image to be registered
Image matching for pattern recognition or image matching in general
G06K9/64A2
Range data matching for pattern recognition
Compounding in ultrasound imaging (relating to noise removal from several ultrasound images)
Mask, wafer positioning, alignment
Devices for aligning tools relative to the circuit board (in PCB manufacturing)
Synonyms and Keywords

In patent documents the following abbreviations are often used:

Recalage (French)
Registration (English)
{using correlation-based methods}
Definition statement
This subclass/group covers:
  • Global correlation
  • Block-matching like correlation, if not for motion analysis

Illustrative example from US2009161988 A1 (applicant ATI Technologies ULC):

media67.png

{using feature-based methods}
Definition statement
This subclass/group covers:
  • "Feature" means significant image region or pixel with certain characteristics.
  • Feature points, e.g. determined by image operators; also matching of point descriptors, feature vectors; significant segments, blobs
  • Feature, landmark, marker, fiducial, edge, corner etc.

Illustrative examples:

  • EP1881453
  • Fig. 3F from WO2007135659 A2 (applicant Elbit Systems Electro-Optics Elop Ltd.):

media68.png

{involving reference images or patches ( image matching for pattern recognition or image matching in general G06K9/64A2) }
Definition statement
This subclass/group covers:

Involving correlation with "true to reality" image patches, templates, regions of interest; correlation used for 1) finding features in each image or for 2) finding regions of interest from one image in the other image

Illustrative examples:

  • US6067373
  • from EP1965350 A1 (applicant Nippon Kogaku KK):

media69.png

References relevant to classification in this group
This subclass/group does not cover:
Correlation of complete images or block-matching-like registration (where blocks are arbitrarily defined by a grid, not as a "meaningful" image region, region of interest)
Informative references
Attention is drawn to the following places, which may be of interest for search:
Image matching for pattern recognition or image matching in general
G06K9/64A2
{involving models ( model matching for pattern recognition G06K9/64A2C , G06K 9/6878) }
Definition statement
This subclass/group covers:
  • Involving matching of intermediary 2D or 3D models extracted from each image before registration, e.g. geometric models of all kinds, polygon models, active appearance and shape models, as opposed to reference images or patches
  • Model matching used for 1) finding features in each image or for 2) finding structure of interest from one image in the other image

Illustrative examples:

  • WO2009052497, EP1772827
  • from US6594378 B1 (applicant Arch Dev Corp.)

media70.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Determining position or orientation of objects involving models
Segmentation or edge detection involving deformable models
Analysis of motion (here: in particular tracking) using models
Model matching for pattern recognition
G06K 9/6878, G06K9/64A2C
{using statistical methods ( image matching by comparing statistics of regions for pattern recognition G06K9/64S) }
Definition statement
This subclass/group covers:
  • Involving probabilistic feature points, statistical features or reference images / patches, statistical models, statistical matching
  • RANSAC

Illustrative examples:

  • WO2006092594, WO0227660
  • Clinton Fookes et al.: "Global 3D Rigid Registration of Medical Images", Proceedings International Conference on Image Processing ICIP, Vancouver, Canada, 10 - 13 Sept. 2000, IEEE, New York, US, 10 Sept. 2000, pp. 447 - 450
  • Russell C. Hardie et al.: "Joint MAP Registration and High-Resolution Image Estimation Using a Sequence of Undersampled Images", IEEE Transactions on Image Processing, vol. 6, no. 12, IEEE, Piscataway, US, Dec. 1997, pp. 1621 - 1632
Informative references
Attention is drawn to the following places, which may be of interest for search:
Image matching by comparing statistics of regions for pattern recognition
G06K9/64S
Special rules of classification within this group

Whenever possible, documents classified herein should also be classified in one of the other subgroups of G06T 7/0024.

{using transform-domain based approaches}
Definition statement
This subclass/group covers:

Fourier, DCT, Wavelet, Gabor etc.: add an Indexing Code from the range of G06T 2207/20048 to G06T 2207/20064 Transform domain processing

Illustrative example: Fig. 1 from US6266452 B1 (applicant NEC Res. Inst. Inc.):

media71.png

{Registration of image sequences}
Definition statement
This subclass/group covers:
  • Aligning one image sequence or image set to the other, i.e. finding spatially or temporally corresponding frames, as opposed to spatial alignment of image frames within a single image sequence
  • Spatial alignment = alignment along the z-axis, e.g. alignment of two stacks of CT slices
  • Temporal alignment = alignment along the t-axis, e.g. alignment of two video sequences
  • Additionally spatially aligning the temporally or spatially corresponding frames in the x-y-plane is possible.

Source sequences can be of any orientation.

Illustrative examples:

  • spatial alignment: US2005169507
  • temporal alignment: US2009185728, FR2895188, WO2006121435
  • left: from US2004184530 A1 (applicant Sarnoff Corp.)
  • right: from EP1623674 A1 (applicant Hitachi Medical Corp.)

media72.png
media73.png

Special rules of classification within this group

Whenever possible, documents classified herein should also be classified in one of the other subgroups of G06T 7/0024.

{Determining position or orientation of objects}
Definition statement
This subclass/group covers:
  • Estimation of pose, posture, attitude
  • Gaze direction, head pose (see also: G06K 9/00221, G06K 9/00597)
  • Bin picking (add the Indexing Code: G06T 2207/30164 Workpiece; Machine component)
  • Repérage (in French documents), location, locating
  • Position or orientation of image content, e.g. an object in the image
  • Position or orientation of the camera (add the Indexing Code G06T 2207/30244: Camera pose)
Informative references
Attention is drawn to the following places, which may be of interest for search:
Image feed-back for automatic industrial control
Gaze direction, head pose determination, if preprocessing for pattern recognition
Orientation detection before recognition
Template matching for pattern recognition
G06K9/64A
Position determination of a camera in a television studio
{using feature-based methods}
Definition statement
This subclass/group covers:

"Feature" means significant image region or pixel with certain characteristics: feature points, edges, corners, e.g. determined by image operators; landmarks, markers, fiducials; significant segments, blobs.

Illustrative examples:

WO2005104033, US2004239756, WO03036384

Fig. 9(A) from US5499306 A (applicant Nippon Denso Co.):

media74.png

{involving reference images or patches ( image matching for pattern recognition or image matching in general G06K9/64A2) }
Definition statement
This subclass/group covers:

Involving correlation with "true to reality" reference images, templates of various poses; for "directly" determining pose; correlation with "true to reality" templates of landmarks, markers, fiducials; for finding features in the image.

Illustrative examples:

  • EP1152371, US6771808 (template of marker), EP1394743 (template called model)
  • left: from EP1043689 A2 (applicant Fanuc Ltd.)
  • right: Fig. 4 from US6771808 B1 (applicant Cognex Corp.)

media75.png
media76.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Image matching for pattern recognition or image matching in general
G06K9/64A2
{involving models ( model matching for pattern recognition G06K9/64A2C , G06K 9/6878) }
Definition statement
This subclass/group covers:
  • Involving matching to a 2D or 3D model, e.g. geometric models of all kinds, polygon models, active appearance and shape models, also abstract models of landmarks, markers, fiducials with spatial extent, as opposed to reference images or patches.
  • Model matching used for 1) finding features in each image or for 2) "directly" determining pose of structure of interest.

Illustrative examples:

  • WO2010006727, US2006259180, WO2008139344, US2001043738 (model matching based on features)
  • from EP2003617 A2 (applicant Canon KK):

media77.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Model matching for pattern recognition
G06K 9/6878, G06K9/64A2C
Model matching for segmentation (takes precedence in case of doubt)
Model matching for tracking
{using statistical methods ( image matching by comparing statistics of regions for pattern recognition G06K9/64S) }
Definition statement
This subclass/group covers:
  • Involving probabilistic feature points, statistical models, statistics of positions
  • Features, reference images, patches or method itself can be statistical

Illustrative examples:

  • US6778699, US2008297507 (model), DE10137656 (model)
  • Clinton Fookes et al.: "Global 3D Rigid Registration of Medical Images", Proceedings International Conference on Image Processing ICIP, Vancouver, Canada, 10 - 13 Sept. 2000, IEEE, New York, US, 10 Sept. 2000, pp. 447 - 450
  • from EP0707284 A2 (applicant Eastman Kodak Co.):

media78.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Image matching by comparing statistics of regions for pattern recognition
G06K9/64S
Probabilistic approaches for segmentation (takes precedence in case of doubt)
Probabilistic approaches for tracking
Special rules of classification within this group

Whenever possible, documents classified herein should also be classified in one of the other subgroups of G06T 7/004.

{Depth or shape recovery}
Definition statement
This subclass/group covers:
  • Shape from X
  • Depth map determination
  • Disparity calculation for shape recovery
Informative references
Attention is drawn to the following places, which may be of interest for search:
Picture taking arrangements specially adapted for photogrammetry or photographic surveying
{from shading}
Definition statement
This subclass/group covers:

Illustrative examples:

  • R. Zhang et al.: "Shade from Shading: a Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 8, pp. 690 - 706, IEEE Service Center, Los Alamitos, CA, USA, August 1999
  • from US5943164 A (applicant Texas Instruments Inc.):

media79.png

{from specularities}
Definition statement
This subclass/group covers:

Illustrative example from EP2120007 A1 (applicant Panasonic Corp.):

media80.png

{from laser ranging and structured images, e.g. interferometry ( image acquisition and arrangements for measuring contours or curvatures of an object by projecting a pattern, thereupon G01B 11/25) }
Definition statement
This subclass/group covers:

"Structured" characterises the illumination.

Illustrative example: Fig. 1 from US2003007159 A1 (applicant Southwest Res. Inst.):

media81.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Image acquisition and arrangements for measuring contours or curvatures of an object by projecting a pattern thereupon
{from texture}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group: from EP2182487 A1 (applicant Quadraxis):

media82.png

{from perspective effects, e.g. using vanishing points}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group: Fig. 5 from EP1959392 A1 (applicant Samsung Electronics Co. Ltd.):

media83.png

{from line drawings}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group: Fig. 3 from US2008166065 A1 (applicant Zygmunt Pizlo et al.):

media84.png

{from multiple images}
Special rules of classification within this group

For documents concerning trilinear computations, trifocal tensor: add the Indexing Code G06T 2207/20088 (Trinocular vision calculations; trifocal tensor)

{from contours}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group: from US2009304265 A1 (applicant Saad M. Khan et al.):

media85.png

References relevant to classification in this group
This subclass/group does not cover:
Shape from contours involving one image only
{from focus}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group: from US2003035576 A1 (applicant Agilent Technologies Inc.):

media86.png
media87.png

{from motion}
Definition statement
This subclass/group covers:
  • Shape from motion, structure from motion
  • Extracting the shape of a scene from the spatial and temporal changes occurring in an image sequence (camera or scene moves)
  • Simultaneous Localisation And Mapping [SLAM] (see also G06T 7/004); add the Indexing Code G06T 2207/30244 Camera pose

Illustrative examples:

  • T. Jebara et al.: "3D Structure from 3D Motion", IEEE Signal Processing Magazine, vol. 16, pp. 66 - 84, IEEE, May 1999
  • Fig. 13 from US6628819 B1 (applicant Ricoh KK)

media88.png

  • from US6952212 B2 (applicant Ericsson Telefon AB L M)

media89.png

{from multiple light sources, e.g. photometric stereo}
Definition statement
This subclass/group covers:
  • Different illumination intensities, e.g. ambient and flash
  • Different directions of illumination

Illustrative example from US2002186878 A1 (applicant Asti Holdings Ltd.):

media90.png

{from stereo images}
Definition statement
This subclass/group covers:

Shape from stereo images or sequences of stereo images-

Illustrative example from WO2011081642 A1 (applicant Thomson Licensing):

media91.png
media92.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Shape from multiple images using trilinear computations / the trifocal tensor
Shape from multiple images using the quadrifocal tensor
{from three or more stereo images}
Definition statement
This subclass/group covers:

Multi-baseline stereo (special case only where

  • each view is always treated together with the same reference view and
  • the lengths of the respective baselines differ from each other)

Illustrative example: Fig. 8 from US6480620 B1 (applicant NEC Corp.):

media93.png

{Segmentation or edge detection ( image analysis based on texture or colour features G06T 7/40 ; motion-based segmentation G06T 7/2006 ; separation of touching or overlapping patterns for pattern recognition G06K 9/34 ; extraction of features or characteristics of the image for pattern recognition G06K 9/46) }
Informative references
Attention is drawn to the following places, which may be of interest for search:
Separation of touching/overlapping patterns for pattern recognition
Extraction of image features/characteristics for pattern recognition
Image analysis based on texture or colour features
Special rules of classification within this group

Allocation of one of symbols G06T 7/0081, G06T 7/0083, G06T 7/0085 is mandatory for segmentation or edge detection; symbols G06T 7/0087 to G06T 7/0097 should be allocated whenever possible.

{Region-based segmentation} ( image analysis based on texture or colour features G06T 7/40 ; separation of touching or overlapping patterns by cutting or merging for pattern recognition G06K 9/342 ; quantising the analogue image signal for pattern recognition G06K 9/38 ; extraction of features or characteristics of the image related to colour for pattern recognition G06K 9/4652)
Definition statement
This subclass/group covers:
  • Thresholding (fixed threshold binarisation, multiple and histogram-derived thresholds: add the Indexing Code G06T 2207/20148 Thresholding)
  • Region growing, splitting and merging
  • Colour-based segmentation

Illustrative example: Fig. 9B from EP2328127 A1 (applicant Rakuten Inc.):

media94.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Separation of touching/overlapping patterns by cutting or merging for pattern recognition
Quantising the analogue image signal for pattern recognition
Extraction of image features/characteristics related to colour for pattern recognition
{Edge-based segmentation ( detecting partial patterns or configurations G06K 9/4604) }
Definition statement
This subclass/group covers:
  • Contour-based segmentation
  • Straight edge-line detection (buildings, roads from aerial images, ...)
  • Finding and linking edge candidate points or segments (edgels)

Illustrative example from US5274742 A (applicant Hitachi Ltd.):

media95.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Detecting partial patterns or configurations
Extracting features by coding the contour of a pattern
{Edge detection ( detecting partial patterns or configurations G06K 9/4604) }
Definition statement
This subclass/group covers:

In contrast to G06T 7/0083, this group covers documents pertaining purely to edge-detection, i.e. not giving any further semantic information related to a particular application, e.g:

  • Derivative methods (first-order or gradient, second order e.g. Laplacian)
  • Zero crossing
  • Corner detection

Illustrative example from EP2098989 A1 (applicant TNO):

media96.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Detecting partial patterns or configurations
Extracting features by coding the contour of a pattern
{involving probabilistic approaches, e.g. Markov Random Field [MRF} modeling ( Markov models or related models or networks embedding Markov models for pattern recognition G06K 9/6297 ; classification techniques based on a parametric, e.g. probabilistic, model G06K 9/6277 ; detecting partial patterns or configurations by analysing connectivity relationship of elements of the pattern G06K 9/4638) ]
Definition statement
This subclass/group covers:

Statistical/Probabilistic methods for segmentation

Illustrative examples:

  • Fig. 2 from US2009196349 A1 (applicant Young-O. Park et al.)

media97.png

  • Fig. 4 from EP1700269 B1 (applicant Eastman Kodak Co.):

media98.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Detecting partial patterns or configurations by analysing connectivity relationship of elements of the pattern
Classification techniques based on a parametric (probabilistic) model
Markov models or related models or networks embedding Markov models for pattern recognition
{involving deformable models, e.g. active contour ( pattern recognition techniques involving a deformation of the sample or reference pattern or elastic matching G06K9/64A2D) }
Definition statement
This subclass/group covers:
  • Model-based segmentation (in particular when applied to biomedical images)
  • Active shape methods: add the Indexing Code G06T 2207/20124 Active shape model [ASM]
  • Active appearance models: add the Indexing Code G06T 2207/20121 Active appearance model [AAM]
  • Active contours, snakes, deformable templates: add the Indexing Code G06T 2207/20116 Active contour; Active surface; Snakes

Illustrative example: Fig. 1 from US2009245638 A1 (applicant Jarrell D. Collier et al.):

media99.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Pattern recognition techniques involving a deformation of the sample or reference pattern or elastic matching
G06K9/64A2D
{involving morphological operators ( combinations of preprocessing functions using a local operator for pattern recognition G06K 9/56) }
Definition statement
This subclass/group covers:

Illustrative examples:

  • from EP1611548 A1 (applicant Koninkl. Philips Electronics NV)

media100.png

  • Fig. 1 from US2007036406 A1 (applicant Siemens Medical Solutions)

media101.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Combinations of pre-processing functions using a local operator for pattern recognition
{involving graph-based approaches ( non-hierarchical partitioning techniques based on graph theory for pattern recognition G06K 9/6224) }
Definition statement
This subclass/group covers:

Graph-cut methods

Illustrative example: Fig. 4 from US2009316988 A1 (applicant Samsung Electronics Co. Ltd.):

media102.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Non-hierarchical partitioning techniques based on graph theory for pattern recognition
{involving transform domain approaches ( detecting partial patterns, e.g. edges or contours, using the Hough transform for pattern recognition G06K 9/4633) }
Definition statement
This subclass/group covers:
  • Fourier-, FFT-, Wavelet-based methods (add an Indexing Code from the range of G06T 2207/20048 to G06T 2207/20064: Transform domain processing)
  • Gabor-, Laplace-transform-based methods,
  • Discrete cosine transform [DCT]-based methods,
  • Walsh-Hadamard transform [WHT]-based methods,
  • Hough transform (detecting partial patterns, e.g. edges or contours, using Hough transform G06K 9/4633).

Illustrative example: Fig. 3 from US6647132 B1 (applicant Cognex Tech. & Investment Corp.):

media103.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Detecting partial patterns, e.g. edges or contours, using Hough transform for pattern recognition
{involving the use of two or more images}
Definition statement
This subclass/group covers:
  • Using information from multiple images to determine segmentation result.
  • Segmentation based on several images taken under varying illumination, focus, exposure, etc.
  • Segmentation of a video frame involving several image frames of the video sequence, e.g. neighbouring frames.
  • Temporal and spatio-temporal segmentation, if not based on motion information.
  • Segmentation using several (neighbouring) slices of a tomographic data set (CT, MRI, PET, etc.), propagation of segmentation results between neighbouring slices.
  • Hierarchical segmentation methods (including wavelet-based schemes), if final segmentation result is derived from (partial) results at different resolution levels.
  • Multispectral image segmentation using information from different spectral bands (beyond the visible spectrum).

Illustrative example from US2009251465 A1 (applicant P. Hassenpflug):

media104.png

References relevant to classification in this group
This subclass/group does not cover:
Motion-based segmentation
Analysis of motion { ( movement detection in television systems H04N 5/144 ; motion estimation for digital video signal compression H04N 7/2676 ; recognizing scenes under surveillance and traffic patterns G06K 9/00771 , G06K 9/00785) }
Definition statement
This subclass/group covers:
  • Change detection
  • Tracking
  • Motion capture
  • Determining camera ego-motion (add the Indexing Code G06T 2207/30244: Camera pose)
  • Medical motion analysis, e.g. of the left ventricle of the heart (add the Indexing Code G06T 2207/30048: Heart; Cardiac)
  • Trajectory representation (add the Indexing Code: G06T 2207/30241 Trajectory)
  • Sports events analysis, movement of players (add the Indexing Code G06T 2207/30221: Sports video; Sports image)
  • Stabilisation of video sequences (see also G06T 7/0024)
References relevant to classification in this group
This subclass/group does not cover:
Shape from motion
Informative references
Attention is drawn to the following places, which may be of interest for search:
Video games
Target following using TV type tracking systems
Light barriers
Data indexing of video sequences
Gesture recognition
Scene recognition
Image registration
{Motion-based segmentation}
Definition statement
This subclass/group covers:
  • Figure/ground segmentation by detection of moving object
  • Partitioning an image into regions of homogenous 2D (apparent) motion
  • Based on analysis of motion vector field or motion flow
  • Grouping from optical flow

Illustrative examples:

  • H. Rom et al., "Motion Based Segmentation", Conference Proceedings Article, pp. 1 - 4, 7 March 1989
  • Fig. 7 from US2007127568 A1 (applicant Toshiba KK):

media105.png

References relevant to classification in this group
This subclass/group does not cover:
Segmentation or edge detection involving the use of two or more images
Informative references
Attention is drawn to the following places, which may be of interest for search:
Segmentation or edge detection
Scene change analysis
{using block-matching}
Informative references
Attention is drawn to the following places, which may be of interest for search:
Use of motion vectors for image compression, coding using predictors, video coding
Movement estimation for television pictures
Predictive coding in television systems using temporal prediction with motion detection
{using full search}
Definition statement
This subclass/group covers:

Full, exhaustive, brute force search

Illustrative example from US2005100095 A1 (applicant Toshiba KK):

media106.png

{using non-full search, e.g. three step search}
Definition statement
This subclass/group covers:
  • Non-full, layered structure, fast, adaptive, efficient search
  • Three-Step, New Three-Step, Four-Step Search
  • Simple and Efficient Search
  • Binary Search
  • Spiral Search
  • Two-Dimensional Logarithmic Search
  • Cross Search Algorithm
  • Adaptive Rood Pattern Search
  • Orthogonal Search
  • One-at-a-Time Algorithm
  • Diamond Search
  • Hierarchical search (add the Indexing Code G06T 2207/20016: Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform)
  • Spatial dependency check

Illustrative example from EP1644896 A2 (applicant Lee Tsu-Chang):

media107.png

{using feature-based methods, e.g. corners, segments}
Definition statement
This subclass/group covers:
  • "Feature" means a significant image region or pixel with certain characteristics
  • Feature points, edges, corners, e.g. determined by image operators; also matching of point descriptors, feature vectors; landmarks, markers, fiducials; significant segments, blobs

Illustrative examples:

  • EP1876567, WO2007110731, WO2008057957
  • from US2008107307 A1 (applicant Sony Corp.):

media108.png

{involving reference images or patches ( image matching for pattern recognition or image matching in general G06K9/64A2) }
Definition statement
This subclass/group covers:
  • Involving correlation of "true to reality" image patches, templates, regions of interest
  • Correlation used for 1) finding features in each image or for 2) finding regions of interest from one image in the other images

Illustrative examples:

  • EP1988505, US2002154820
  • from US2002154820 A1 (applicant Toshiba KK):

media109.png

References relevant to classification in this group
This subclass/group does not cover:
Block-matching (where blocks are arbitrarily defined by a grid, not as a "meaningful" image region)
Informative references
Attention is drawn to the following places, which may be of interest for search:
Face recognition using comparisons between temporally consecutive images
Image matching for pattern recognition or image matching in general
G06K9/64A2
{involving models ( model matching for pattern recognition G06K9/64A2C , G06K 9/6878) }
Definition statement
This subclass/group covers:
  • Involving matching of intermediary 2D or 3D models extracted from each image before motion analysis, e.g. skeletons, stick models, ellipses, geometric models of all kinds, polygon models, active appearance and shape models, as opposed to reference images or patches
  • Model matching used for 1) finding features in each image or for 2) finding structure of interest from one image in the other images

Illustrative examples:

  • US2008069436, US5625577
  • from US2009220124 A1 (applicant Fred Siegel):

media110.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Model matching for pattern recognition
G06K 9/6878, G06K9/64A2C
{involving subtraction of pictures}
Definition statement
This subclass/group covers:
  • Subtraction of previous image
  • Subtraction of background image, background maintenance, background models therefor
  • Also involving ratio or more general comparison of corresponding pixels in successive frames

Illustrative example from EP1868158 A2 (applicant Toshiba KK):

media111.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Change detection in biomedical image inspection
Actuation of alarms using motion detection systems
G08B13/194C
{using transform domain based approaches, e.g. Fourier}
Definition statement
This subclass/group covers:
  • Fourier, DCT, Wavelet, Gabor etc.: add an Indexing Code from the range of G06T 2207/20048 to G06T 2207/20064 Transform domain processing
  • Using phase correlation

Illustrative examples:

  • Fig. 6 from EP2207139 A1 (applicant Vestel Elekt Sanayi Ve Ticaret)

media112.png

  • Fig. 1 from EP1659535 A2 (applicant Mitsubishi Electric Inf. Tech., Mitsubishi Electric Corp.):

media113.png

{using gradient-based methods}
Definition statement
This subclass/group covers:

Optic (optical) flow involving the calculation of spatial and temporal gradient

Illustrative examples:

  • equation 1 from EP0966727 B1 (applicant GMD GmbH)

media114.png

  • from EP1361543 A2 (applicant Matsushita Electric Ind. Co. Ltd.):

media115.png

{Motion estimation over a hierarchy of resolutions}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group: Fig. 2 from US2009324013 A1 (applicant Fujifilm Corp.):

media116.png

{involving a stochastic approach, e.g. Kalman filter}
Definition statement
This subclass/group covers:
  • Bayesian methods
  • HMM
  • Particle filtering

Illustrative example: Fig. 5 from US2009175500 A1 (Illustrative example of particle filtering, applicant Victor Company of Japan):

media117.png

Special rules of classification within this group

Whenever possible, documents classified herein should also be classified in one of the other subgroups of G06T 7/20.

{Computing motion from a sequence of stereo images}
Definition statement
This subclass/group covers:

Illustrative example of subject matter classified in this group from US2006215903 A1 (applicant Toshiba KK):

media118.png

[Multi-camera tracking]
Definition statement
This subclass/group covers:
  • Algorithms for camera networks
  • Interaction, cooperation between trackers
  • Multi-view tracking, multi-camera tracking
  • The cameras view the same scene (cooperation e.g. by voting, epipolar constraint, fusion)
  • The cameras view different scenes (cooperation e.g. by handover, tracklet joining, trajectory joining)

Illustrative examples:

  • US7450735, US2009268033, US2008172384
  • Fig. 1 from WO2009070560 A1 (applicant NEC Lab America Inc.):

media119.png

References relevant to classification in this group
This subclass/group does not cover:
Cooperative motion analysis from a single stereo camera pair
Motion analysis from at least three views, wherein at least one pair of views is processed as stereo pair
Informative references
Attention is drawn to the following places, which may be of interest for search:
Face recognition of unknown faces across different face tracks
Special rules of classification within this group

Whenever possible, documents classified herein should also be classified in one of the other subgroups of G06T 7/20.

In particular, in the case of motion analysis from multiple monocular views with subsequent merging or joining of analysis results, details about the respective analysis algorithm per view should be classified in the subgroups of G06T 7/20 as well.

Analysis of texture { ( depth or shape from texture G06T 7/0059) }
References relevant to classification in this group
This subclass/group does not cover:
Shape from shading
Shape from texture
Informative references
Attention is drawn to the following places, which may be of interest for search:
Colour / texture segmentation
{based on statistical texture description}
Definition statement
This subclass/group covers:

Illustrative examples of subject matter classified in this group:

  • L. van Gool et al.: "Survey Texture Analysis Anno 1983", Computer Graphics, Vision, and Image Processing, vol. 29, no. 3, Academic Press, Duluth, MA, US, March 1985, pp. 336 - 357
  • M. Tuceryan, A. K. Jain: "The Handbook of Pattern Recognition and Computer Vision", 2nd edition (eds. C. Pau et al.), World Scientific Publishing Co., 1998, pp. 207 - 248 (Chapter 2.1: Texture Analysis)
  • Materka, M. Strzelecki: "Texture Analysis Methods - A Review", Technical University of Lodz, Institute of Electronics, COST B11 Report, Brussels 1998, pp. 1 - 33
Special rules of classification within this group

The classification symbol G06T 7/401 is allocated to documents concerning:

  • First-order statistics
  • Global histogram-based measures: mean, variance, skewness, kurtosis, energy, entropy
  • Autocorrelation
  • Run-length based algorithms
{using transform-domain based approaches}
Definition statement
This subclass/group covers:

Fourier, DCT, Wavelet, Gabor, etc.: add an Indexing Code from the range of G06T 2207/20048 to G06T 2207/20064 Transform domain processing

Illustrative example: Fig. 2 from WO0141071 A1, also published as EP1159709 A4 (applicant Samsung Electronics Co. Ltd. et al.):

media120.png

{using image operators, e.g. filter, edge density, local histograms}
Definition statement
This subclass/group covers:
  • Laws texture energy measure
  • Texture analysis using edge operators
  • Texture analysis using difference of Gaussians
  • Texture analysis using local linear transforms
  • Local Binary Pattern [LBP]
  • Grey level difference method
  • Local rank order correlation
{using co-occurrence matrix computation}
Definition statement
This subclass/group covers:
  • Second-order statistics
  • Generalised co-occurrence matrix
{using random Fields}
Definition statement
This subclass/group covers:
  • Markov Random Fields, Gaussian Random Fields, Gibbs Random Fields
  • Autoregressive Model
{based on structural texture description, i.e. primitives and placement rules}
Definition statement
This subclass/group covers:
  • Shape chain grammars, graph grammars
  • Grouping of primitives in hierarchical textures

Illustrative examples:

  • L. van Gool et al.: "Survey Texture Analysis Anno 1983", Computer Graphics, Vision, and Image Processing, vol. 29, no. 3, Academic Press, Duluth, MA, US, March 1985, pp. 336 - 357
  • M. Tuceryan, A. K. Jain: "The Handbook of Pattern Recognition and Computer Vision", 2nd edition (eds. C. Pau et al.), World Scientific Publishing Co., 1998, pp. 207 - 248 (Chapter 2.1: Texture Analysis)
  • Materka, M. Strzelecki: "Texture Analysis Methods - A Review", Technical University of Lodz, Institute of Electronics, COST B11 Report, Brussels 1998, pp. 1 - 33
  • from EP1391844 A2 (applicant LSI Logic Corp.):

media121.png

{Color analysis}
Definition statement
This subclass/group covers:
Informative references
Attention is drawn to the following places, which may be of interest for search:
Correct redeye defect
Colour image segmentation
Recognising eye features
Analysis of geometric attributes, e.g. area, center of gravity or perimeter, from an image
Informative references
Attention is drawn to the following places, which may be of interest for search:
Measuring arrangements by the use of optical means
Extracting geometrical properties from the whole image as recognition features
Special rules of classification within this group

The classification symbol G06T 7/60 is allocated to documents concerning: Ellipse detection

{Area, perimeter, diameter or volume}
Definition statement
This subclass/group covers:

Illustrative examples of subject matter classified in this group:

  • WO2008072157, EP2098993
  • Fig. 9 from US2009180677 A1 (applicant Fuji Film Co. Ltd.):

media122.png

{Convexity or concavity}
Definition statement
This subclass/group covers:

Convexity, concavity, curvature, circularity, sphericity, roundness

Illustrative examples:

  • US2005259856, WO2005015500, EP1873483
  • Fig. 5 from US2005053270 A1 (applicant Konica Minolta Med. & Graphic):

media123.png

  • from EP1785940 A2 (applicant General Electric Company):

media124.png

{Center of gravity or moments ( moments specific for pattern recognition, e.g. Zernike moments G06K 9/525) }
Definition statement
This subclass/group covers:

Following centers of gravity of sections along elongated or tubular structure

Illustrative examples:

  • US2009022406, US2008131002
  • V. Tuzikov et al.: "Computation of volume and surface body moments", Pattern Recognition, vol. 36, no. 11, Elsevier, November 2003, pp. 2521 - 2529
  • Fig. 19 from US2007253610 A1 (applicant Interact Medical Technologies Corp.):

media125.png

Informative references
Attention is drawn to the following places, which may be of interest for search:
Moments specific for pattern recognition, e.g. Zernike moments
{Symmetry}
Definition statement
This subclass/group covers:
  • Determination of lines of symmetry, midlines
  • Measurement of symmetry and asymmetry

Illustrative examples:

  • US2008021502, US2003149947
  • Fig. 5 of US2009174707 A1 (applicant Prec Light Inc.):

media126.png

Image coding, e.g. from bit-mapped to non bit-mapped ( {H04N 1/00 , H04N 19/00 take precedence; } compression in general H03M; compression for image communication H04N)
Definition statement
This subclass/group covers:

Coding/compression and decoding/decompression of computer graphics(CG) data and computer graphics compression methods applied on natural image/video.

Apparatus/devices of coding/compressing and/or decoding/decompressing of computer graphics data.

Computer graphics data mentioned including:

  • object geometry models
  • scene models
  • 2D/3D vector graphics
  • 3D/4D volumetric models
  • CAD models
  • contour shape data
  • elevation data
  • CG related metadata/parameters including depth, colour, texture, motion vectors, scene graph, position, connectivity information and similar.
Relationship between large subject matter areas

This group covers compression/coding/decompression/decoding of CG related data and CG related methods applied on natural image or video. Other compression techniques specific to the natural image/video without using CG related methods are covered by H04N 7/26.

Compression in general is covered by H03M 1/00.

References relevant to classification in this group
This subclass/group does not cover:
Computer aided design
Pattern recognition
Animation
Rendering of computer graphics data
Modeling of computer graphics data
Manipulation 3D objects
Compression in general
Transmission of TV signals
Selective content distribution
Informative references
Attention is drawn to the following places, which may be of interest for search:
Pattern recognition by contour coding
Re-meshing for manipulation, editing purpose
Shape/contour coding
Model based coding
Model based coding using a 3D model
Scene description coding
Hybrid coding of synthetic and natural picture components
Tree coding
Fractal coding
Vector coding
Special rules of classification within this group

In general, consult the gérant before using any sub-groups. This is a provisionary document which will be replaced in January, 2012, after completing reorganization in G06T 9/00.

  • for classification, the main group G06T 9/00 is assigned always before completing the reorganization.
  • The Indexing Code series S06T209/00 of symbols is reserved for the use of documents classified in G06T 9/00 and subgroups. They should be allocated to documents in G06T 9/00 and subgroups whenever relevant.
  • the sub-groups G06T 9/004, G06T 9/005, G06T 9/005, G06T 9/008 are not used anymore, the content, which is not related with computer graphics data compression/coding, will be transferred to the corresponding classes defined in the group definition statements below.
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
4D volumetric models
Sequences of volumetric images over time
MPEG
Moving Picture Experts Group
SNHC
Synthetic/Natural Hybrid Coding
BIFS
Binary Format for Scene
VRML
Virtual Reality Modeling Language
SVG
Scalable Vector Graphics
NN
Neural Networks
TV
Television
Synonyms and Keywords

In patent documents the following abbreviations are often used:

CG
Computer graphics
3D
Three dimensional
4D
Four dimensional
CAD
Computer aided design

In patent documents the following expressions/words:

  • "Compression" and "Coding"
  • "Decompression" and "Decoding"
  • "Scene graph" and "Scene model"
  • "Scene description graph" and "Scene graph"
  • "Metadata" and "Parameter"
  • "Contour coding" and "Shape coding"
  • "Elevation data" and "Height data"
  • "Object geometry models" and "Object models"
  • "Natural image" and "Raster/Bitmap image"
  • "Vector graphics" and "Scalable Vector Graphics"

are often used as synonyms.

{Model-based coding, e.g. wire frame ( see provisionally also G06T 9/00) }
Definition statement
This subclass/group covers:

Means or steps for the compression/coding of wire frame models, e.g. polygon meshes.

Documents concerning mesh compression/coding by

  • face merging
  • incremental decimation
  • simplification by remeshing for data reduction purpose are classified here.
References relevant to classification in this group
This subclass/group does not cover:
Animation
Rendering of computer graphics data
Re-meshing for manipulation, editing
Manipulation 3D objects
Informative references
Attention is drawn to the following places, which may be of interest for search:
Model based coding
Model based coding using a 3D model
Special rules of classification within this group

Documents classified in H04N 7/26654 and H04N 7/26659 are transferred to G06T 9/001.

Documents concerning re-meshing for manipulation, editing and similar, i.e. all means not having data reduction purpose are classified in G06T 17/205.

Synonyms and Keywords

In patent documents the following expressions/words "wireframe" and "polygon mesh" are often used as synonyms.

{using neural networks}
Definition statement
This subclass/group covers:

Means or steps for the compression/coding of computer graphics data and natural image/video data using neural networks (NN).

Special rules of classification within this group

The compression/coding data concerning in this group includes:

  • computer graphics data
  • natural image/video data.
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
NN
Neural Networks
{Predictors, e.g. intraframe, interframe coding ( see provisionally also G06T 9/00) }
Definition statement
This subclass/group covers:

This group is not used anymore, its content, which is not related with computer graphics data compression/coding, are transferred to H04N 7/26015, H04N 7/26021 or H04N 7/26031.

Informative references
Attention is drawn to the following places, which may be of interest for search:
Predictor
Coding or prediction mode selection
Intracode mode selection
Special rules of classification within this group

This sub-group is not used anymore.

{Statistical coding, e.g. Huffman, run length coding ( see provisionally also G06T 9/00) }
Definition statement
This subclass/group covers:

This group is not used anymore, its content, which is not related with computer graphics data compression/coding, will be transferred to H04N 7/26106.

Informative references
Attention is drawn to the following places, which may be of interest for search:
Variable length coding (VLC) or entropy coding
Special rules of classification within this group

This sub-group is not used anymore.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
VLC
Variable length coding
{Transform coding, e.g. discrete cosine transform ( see provisionally also G06T 9/00) }
Definition statement
This subclass/group covers:

This group is not used anymore, its content, which is not related with computer graphics data compression/coding, will be transferred to H04N 7/30.

Informative references
Attention is drawn to the following places, which may be of interest for search:
Transform coding
Special rules of classification within this group

This sub-group is not used anymore.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
DCT
Discrete cosine transform
{Vector quantisation ( see provisionally also G06T 9/00) }
Definition statement
This subclass/group covers:

This group is not used anymore, its content, which is not related with computer graphics data compression/coding, will be transferred to H04N 7/28.

Informative references
Attention is drawn to the following places, which may be of interest for search:
Vector coding
Special rules of classification within this group

This sub-group is not used anymore.

Synonyms and Keywords

In patent documents the following expressions/words "vector coding" and "vector quantization" are often used as synonyms.

Contour coding, e.g. using detection of edges
Definition statement
This subclass/group covers:

Means or steps for the compression/coding of computer graphics data using contour/shape coding method, e.g. by detection of edges.

Informative references
Attention is drawn to the following places, which may be of interest for search:
Shape coding for video objects
Special rules of classification within this group

Documents classified in H04N 7/26643 are transferred to G06T 9/20.

The compression/coding data concerning in this sub-group includes:

  • computer graphics data, e.g. vector graphics data
  • natural image/video data.
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
SVG
Scalable Vector Graphics
Synonyms and Keywords

In patent documents the following expressions/words "contour coding" and "shape coding" are often used as synonyms.

In patent documents the following expressions/words "vector graphics" and "scalable vector graphics" are often used as synonyms.

Tree coding, e.g. quadtree, octree ( see provisionally also G06T 9/00)
Definition statement
This subclass/group covers:

Means or steps for the compression/coding of computer graphics data by using a tree hierarchy, e.g. quadtree, octree, and similar.

The documents concerning compression/coding of:

  • computer graphics object models, scene models and related metadata, e.g. depth data,

are classified here.

References relevant to classification in this group
This subclass/group does not cover:
Modelling by tree structure
Natural image/video tree coding
Informative references
Attention is drawn to the following places, which may be of interest for search:
Tree description
Tree coding
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Bintree or binary tree
tree structure in which each node has at most two child nodes
Quadtree or quad tree
tree structure in which each node has at most four child nodes
K-tree
tree structure in which each node has at most K child nodes
Hextree
tree structure in which each node has at most six child nodes
Volume octree
tree structure in which each voxel is subdivided into at most 8 subvoxels
Surface octree
Volume octree with incorporated surface information
Multi tree
directed acyclic graph in which the set of nodes reachable from any node forms a tree
Synonyms and Keywords

In patent documents the following expressions/words "scene graph", "scene description graph" and "scene model" are often used as synonyms.

2D [Two Dimensional] image generation
Definition statement
This subclass/group covers:

Documents dealing with generating a 2D image or texture in general. To a large extend, but not exclusively, G06T 11/00 covers image generation "from a description to a bit-mapped image" in general.

Further to documents not otherwise provided for in the subgroups, the following topics:

  • Software packages, systems
  • Caricaturing, Identikit
  • Fusion of images with different objects, e.g. fusion of real and virtual images, labelling of 2D images
  • Clipping of 2D images

It further includes reconstruction from projections, e.g. for computed tomography.

It is also for device independent techniques, i.e. it is not for documents which are specially adapted e.g. for printers, scanners or displays.

Simply speaking, the general idea for G06T 11/00 is:

For generating an image, you

References relevant to classification in this group
This subclass/group does not cover:
Generating of panoramic or mosaic images
Video editing
Colour space manipulation
Studio circuits for video generation, mixing and special effects
Informative references
Attention is drawn to the following places, which may be of interest for search:
Input arrangements or combined input and output interaction between user and computer (user interfaces)
{Texturing; Colouring; Generation of texture or colour}
Definition statement
This subclass/group covers:

Texture generation

  • Textures; endless, periodic pattern
  • Brush strokes
  • Fractals; Julia sets; Koch curves

Colour generation, changing of selected colours

  • Colour palettes, schemes; colour LUT; CLUT
  • False colours
  • Simulation of watercolour, oil paint, airbrush
References relevant to classification in this group
This subclass/group does not cover:
Inpainting
Colour palettes, CLUTs for displays
Colour space manipulation
Informative references
Attention is drawn to the following places, which may be of interest for search:
Antialiasing of lines
Texture mapping
Colour modifications in 3D images or models
Antialiasing using filters
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
LUT
look-up table
CLUT
colour look-up table
{Reconstruction from projections, e.g. tomography}
Definition statement
This subclass/group covers:
  • Reconstruction from tomographic projections, i.e. measurements of an unknown object function integrated along lines (= Radon transform), e.g. density, activity distribution.
  • Refraction tomography
  • for CT, SPECT, PET, Tomosynthesis
References relevant to classification in this group
This subclass/group does not cover:
Image enhancement in general
Depth or shape recovery from multiple images
Image analysis, incl. biomedical image inspection, image registration, segmentation, analysis of motion, analysis of geometric attributes
Medical informatics
NMR
Measuring X-radiation
Analysis of materials using tomography
Impedance measuring for diagnostic purposes
Diagnosis, mechanics
Echography, ultrasound
Special rules of classification within this group

Further details on the subgroups:

G06T 11/005 is used for:

  • Calibration
  • Source positioning
  • Synchronisation
  • Scouts
  • Rebinning
  • Scatter correction
  • Attenuation correction
  • Fourier methods
  • Algebraic methods
  • Back-projection
  • Statistical Methods, e.g. maximum likelihood
  • Compressed sensing, sparsity
  • Processing which relies essentially on unique properties of tomographic images, e.g. projection geometry or interactions of radiation with matter
  • Voxelisation
  • Artefact correction (e.g. metal, cone-beam)

The following list of symbols from the series S06T211/4xx should be allocated to documents in G06T 11/003 whenever relevant:

  • G06T 2211/404 angiography - Angiographic reconstruction: This keyword includes all the reconstruction methods concerning vessels, tree structures etc.
  • G06T 2211/408 dual energy - Reconstruction from dual or multi energy acquisition, polychromatic X-rays
  • G06T 2211/412 dynamic - Dynamic reconstruction: Moving objects are involved or motion compensation is required (e.g.: heart, lung movement, etc...)
  • G06T 2211/416 exact reconstruction - Exact or quasi-exact reconstruction algorithms (in contrast to approximate algorithms)
  • G06T 2211/421 fbp - Filtered Back Projection based methods (the projection data can be handled sequentially, view-by-view)
  • G06T 2211/424 iterative - Iterative methods including all the methods using iterations independent of the reconstruction method per-se.
  • G06T 2211/428 real-time - Real time reconstruction, e.g. fluoroscopy
  • G06T 2211/432 truncation - All or part of the data from the detectors are truncated/incomplete projection data.
  • G06T 2211/436 limited angle - limited-angle or few view acquisition
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
CT
Computed Tomography
NMR
Nuclear Magnetic Resonance
MRI
Magnetic Resonance Imaging
SPECT
Single-Photon-Emission Computed Tomography
PET
Positron Emission Tomography
Drawing from basic elements, e.g. lines or circles
Definition statement
This subclass/group covers:

This group is almost empty and only contains the documents that don't fit well into the following two sub-groups:

{Drawing of straight lines or curves}
Definition statement
This subclass/group covers:
  • Scan conversion of vectors, lines, ellipses, circles (FvD 3.2 - 3.4)
  • Offset, contour curves
  • Wide, thick lines or strokes (FvD 3.9, 19.2.7)
  • Splines, B-splines, NURBS; Bézier, algebraic, parametric, polynomial, cubic curves; control points
  • Approximation of curves or polygons
  • Antialiasing, dejagging of lines; supersampling; subpixel or area weighting (FvD 3.17, 19.3)
  • Font rendering, e.g. scalable, outline, contour, edge fonts (FvD 19.4)
  • Sketching; freehand curve drawing
References relevant to classification in this group
This subclass/group does not cover:
Font handling
Printer fonts
Feature extraction by contour coding
Vector coding
Display character generators
Informative references
Attention is drawn to the following places, which may be of interest for search:
Filling a planar surface by adding surface attributes
{Drawing of charts or graphs}
Definition statement
This subclass/group covers:
  • Diagram, graph layout; directed graph; flow graph; flowchart
  • Venn diagram; nested tree-map
  • Pie, tile, column, bar, business charts
  • 2D and 3D Visualization of data; fluid flows; vector fields; scattered data
  • Sketched diagrams or graphs
References relevant to classification in this group
This subclass/group does not cover:
Navigational instruments, e.g. for aircrafts
Menu systems, graphical querying
Reports for medical diagnosis
G06F19/00M3R
Visualization for Bioinformatics
Input devices, GUIs
GUI programs, e.g. file browsers
Animation of fluid flows
Network visualisation or monitoring
Informative references
Attention is drawn to the following places, which may be of interest for search:
Manipulating of 3D models or images for Computer Graphics
Administration, e.g. office automation or reservations; resource or project management
Finance, e.g. banking, investment or tax processing; Insurance, e.g. risk analysis or pensions
Filling a planar surface by adding surface attributes, e.g. colour or texture
Definition statement
This subclass/group covers:
  • Polygon scan conversion; rasterisation (see e.g. FvD 3.6, 15.6)
  • Scan-line algorithms, fragment processing
  • Antialiasing, supersampling, subpixel or coverage masks (FvD 3.17)
  • Tile-based rendering
  • Filling of a polygon, rectangle, circle, ellipse, region, area, shape
  • Interior/exterior determination; edge lists or edge flags
  • Colouring flat cartoons
  • Seed filling
  • Drawing of space-filling curves; Peano, Hilbert, Serpinski curves
References relevant to classification in this group
This subclass/group does not cover:
Control of the frame buffer(s)
Informative references
Attention is drawn to the following places, which may be of interest for search:
Drawing or scan conversion of lines and fonts
3D image rendering (architectures)
Synonyms and Keywords

In patent documents the terms "rasterising", "scan conversion" and "rendering" are often used as synonyms.

Editing figures and text; Combining figures or text
Definition statement
This subclass/group covers:
  • Bitmap editors
  • Page layout, page composition, e.g. photo-album, collages, business or greeting cards
  • Combining small images by editing in order to generate a new (big) one
  • 2D cosmetic or hairstyle simulations
  • Editing of vector graphics
  • Electronic or desktop publishing (DTP), Page Description Language (PDL), PostScript, TeX (see e.g. FvD 19.9)
References relevant to classification in this group
This subclass/group does not cover:
Face sketching with eye witnesses
Formatting, i.e. changing representation of documents
Form filling
Input devices, GUIs
PDL specifically for printers
Mosaic or panoramic images
Image registration
Video editing
Composing, repositioning or geometrically modifying originals
Informative references
Attention is drawn to the following places, which may be of interest for search:
Medical image archiving systems, e.g. PACS, DICOM
G06F19/00M5I
Document analysis
G06K9/20L
Annotating 3D objects with text
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
DTP
Desktop Publishing
PDL
Page Description Language
Creating or modifying a manually drawn or painted image using a manual input device, e.g. mouse, light pen, direction keys on keyboard
Special rules of classification within this group

This group is not used for classification. Its subject-matter is covered by G06F 3/00 and subgroups

Animation
Definition statement
This subclass/group covers:

Generating and displaying a sequence of images of artwork or model positions in order to create the effect of movement in a scene.

Animation of data representing a 3D or 2D image model or object.

Time related computation of 2D or 3D images, generation of a sequence of 2D or 3D images is classified in this group.

This group is also given as classification to indicate that animation aspects are present but the invention lies in another group than G06T 13/00.

Documents only dealing with motion capture (for animation) are not classified in G06T 13/00(the generation of an animation has to be part of the document to be classified here).

References relevant to classification in this group
This subclass/group does not cover:
Motion capture (for animation)
Navigation in virtual worlds
Processing a sequence of stereoscopic images
Informative references
Attention is drawn to the following places, which may be of interest for search:
Video games
Computer aided design using simulation
3D modelling for computer graphics
Manipulation of 3D models for computer graphics
Geometric image transformations for image warping
Model based coding of video objects
Special rules of classification within this group

Deforming meshes for animation purposes get both classifications: G06T 13/00 or one of its subgroups and G06T 17/20.

The series G06T 2213/00 of Indexing Codes is reserved for the use of documents classified in G06T 13/00 and subgroups. They should be allocated to documents in G06T 13/00 and subgroups whenever relevant:

Indexing scheme for animation: SHOULD BE EMPTY!
animation software package: soft- or hardware packages for animation
rule based animation: e.g. rules for behaviour, script, personality
animation description languages: computer languages for the description of an animation

Furthermore, Indexing Codes from the series G06T 2200/00 and G06T 2210/00 should be allocated to documents whenever relevant. Specific symbols from these series that are especially relevant for the documents in a certain subgroup are mentioned under the "Specific rules for classification" of the respective subgroups.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Animation system
traditional animation systems are based on key-frames, which are a succession of individual states (the position, orientation, and current shape of objects) specified by an animator or user
Synonyms and Keywords

In patent documents the following words/expressions "simulation (of motion)" and "animation" are often used as synonyms.

3D [Three Dimensional] animation
Definition statement
This subclass/group covers:

Subject matter wherein the animated image data presents a three-dimensional image model or object.

Means or steps for the generation of a sequence of 3D images.

Documents in this group concern the generation of an animation of 3D objects in general and articulated 3D objects not representing characters.

Simulations with 3D objects (e.g. bouncing balls) or 2D surfaces in 3D space (e.g. cloth) are classified here.

References relevant to classification in this group
This subclass/group does not cover:
Nominally claimed subject-matter directed to animation with significant user interaction or manipulation
Informative references
Attention is drawn to the following places, which may be of interest for search:
Coding of wireframe meshes for animation
Simulating properties, behaviour or motion of objects in video games
Special rules of classification within this group

For documents concerning both 2D and 3D animation of objects the first place priority rule is applied, i.e. they are classified only in G06T 13/20 or its subgroups.

Documents where cloth moves according to wind effects are classified in both subgroups G06T 13/20 and G06T 13/60.

For specific aspects of documents in this group the following additional Indexing Codes from the series G06T 2210/00 should be allocated to documents in G06T 13/20 and subgroups whenever relevant:

For animation of cloth: G06T 2210/16

For collision of 3D objects: G06T 2210/21

For fluid flows: G06T 2210/24

For animation using particles: G06T 2210/56

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
CFD
Computational fluid dynamics
{driven by audio data}
Definition statement
This subclass/group covers:

Means or steps for the generation of an animation sequence based on audio data.

The input is audio data, e.g. music, speech data, i.e. no written text.

Changes e.g. in motion, colour, shape or position of objects in the animation are generated based on time events in the audio data, e.g. the beat in the music or the change of instrumentation.

References relevant to classification in this group
This subclass/group does not cover:
Electrophonic musical instruments
Emotion analysis from speech for face animation or talking heads
G10L17/00C
Lip-synchronization or synthesis of lip shapes (visemes) from speech for face animation or talking heads
G10L21/06L
Informative references
Attention is drawn to the following places, which may be of interest for search:
Animation based on written text
Video editing or indexing or timing
Special rules of classification within this group

Documents where the audio input animates a 2D object are classified in both subgroups G06T 13/205 and G06T 13/80.

of characters, e.g. humans, animals or virtual beings
Definition statement
This subclass/group covers:

Subject matter wherein the animated object exhibits lifelike motions or behaviours.

Means or steps for the generation of an animation sequence of articulated objects representing virtual characters or for the generation of an animation sequence of "body" parts.

The animated characters herein include, e.g. humans, animals or virtual beings.

Animation of a character normally consists of an articulated skeleton surrounded by an implicitly defined volume or a wireframe surface mesh.

Lifelike motions include walking, running, waving or talking. Lifelike behaviours include showing emotions or reactions to events.

Animation of e.g. faces, lips, eyes, gestures, hair or feathers on a character.

Documents concerning only the synthesizing aspect of character animations for Tele- or Videoconferencing (no image capturing, no data transmission)

References relevant to classification in this group
This subclass/group does not cover:
Interaction of avatars in virtual worlds
Interaction of avatars in virtual worlds for business
Tele- or Video-conferencing
Informative references
Attention is drawn to the following places, which may be of interest for search:
Head tracking input arrangements for interaction between user and computer
Eye tracking input arrangements for interaction between user and computer
Animation of articulated objects in general, i.e. not exclusively or not with the main application for character animation
Garment try-on simulators
Emotion analysis from speech for face animation or talking heads
G10L17/00C
Lip-synchronization or synthesis of lip shapes (visemes) from speech for face animation or talking heads
G10L21/06L
Computing the motion of game characters with respect to other game characters, virtual objects or elements of a game scene
Special rules of classification within this group
  • Documents where the characters are only 2D are classified in both subgroups G06T 13/40 and G06T 13/80.
  • Documents where the hair on a character is moved by wind effects are classified in both subgroups G06T 13/40 and G06T 13/60.
  • Documents where the animation data for the character results from motion capture of real characters are classified in both subgroups G06T 7/00 and G06T 13/40.
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Avatar
graphical representation of the user or the user's character
(inverse) kinematics
calculates the motions necessary to achieve a desired position of the character
Mocap
motion capture
Motion retargeting
transferring the motion from one character to another, different one
Skeleton
tree structure composed of several joints to facilitate modelling the motion of the character
Skinning
technique to deform the skin from the deformation of the skeleton
Synonyms and Keywords

In patent documents the following words "Avatar" and "character" are often used as synonyms.

of natural phenomena, e.g. rain, snow, water or plants
Definition statement
This subclass/group covers:

Subject-matter wherein the animated images are associated with natural phenomena.

Means or steps for the generation of a simulation of natural elements or phenomena.

Documents concerning:

  • the simulation of rain, water, foam, water waves, clouds, fog, snow, fireworks, explosions or
  • wind effects on grass, plants, flags or hair or
  • growing processes of plants or beings or
  • destruction processes

are classified here.

References relevant to classification in this group
This subclass/group does not cover:
Physical forces (other than wind) acting on 3D objects, e.g. simulation of a flying bullet or bouncing of a ball
The simulation of behavioural effects of characters, e.g. the flee behaviour of sea anemons
Informative references
Attention is drawn to the following places, which may be of interest for search:
Computer aided design using simulation
Simulation of fluid flows in general (3D flows)
Simulation of fluid flows in general (2D flows)
Special rules of classification within this group

Documents where the hair on a character is moved by wind effects are classified in both subgroups G06T 13/40 and G06T 13/60.

Documents where cloth moves according to wind effects are classified in both subgroups G06T 13/20 and G06T 13/60.

For specific aspects of documents In this group the following additional Indexing Codes from the series G06T 2210/00 should be allocated whenever relevant:

For fluid flows: G06T 2210/24

For animation using particles, e.g. fireworks, dust: G06T 2210/56

For weathering effects like e.g. aging, corrosion: G06T 2210/64

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Weathering
aging process of material by exposure to weather, e.g. wind, water, certain temperatures
2D [Two Dimensional] animation, e.g. using sprites
Definition statement
This subclass/group covers:
  • Subject matter wherein the animated image data is a 2D image object.
  • Means or steps for time related computation of a sequence of 2D images, e.g. a small moveable 2D graphic pattern on a display, often used in video game animation.
  • Generation of 2D animated cartoons.
  • Animation of 2D text, 2D letters.
  • Change over in slide shows, leafing through digital photo albums.
  • General aspects of 2D morphing or keyframe interpolation.
  • All documents exclusively dealing with the animation of 2D images, i.e. no 3D animation.
  • Generation of 2D motion blur.
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geometric image transformations for image warping
Video editing or indexing or timing
Special rules of classification within this group
  • Documents where the animated 2D object is a character, i.e. 2D character animation, are classified in both subgroups G06T 13/40 and G06T 13/80.
  • Documents where the motion blur concerns only the background image are classified in both subgroups G06T 13/20 and G06T 13/80.
  • Documents where the audio input animates a 2D object are classified in both subgroups G06T 13/205 and G06T 13/80.
  • For documents concerning both 2D and 3D animation of objects with similar algorithms the first place priority rule is applied, i.e. they are classified only in G06T 13/20 or its subgroups, not in G06T 13/80.
  • Documents concerning morphing or warping are additionally classified with the Indexing Code G06T 2210/44.
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Keyframe interpolation
generation of a smooth transition between a starting and an ending keyframe
Morphing
continuous transformation between images (shape and colour)
Sprite
2D image or animation that is integrated into a larger 2D scene
Warping
geometric transformation of the 2D object shape
Synonyms and Keywords

In patent documents the following expressions are often used as synonyms:

  • "Keyframe interpolation" and "inbetweening"
  • "Morphing" and "warping"
3D [Three Dimensional] image rendering
Definition statement
This subclass/group covers:

Means or steps for generating a displayable monoscopic image from a 3D model or 3D data set.

The 3D model is a description of three-dimensional objects in a strictly defined language or data structure.

A 3D data set may include voxel data.

Included in this group are input data sets of 3D coordinates or higher.

This group covers the geometry subsystem of the graphics rendering pipeline, i.e. modeling transformation, lighting, viewing transformation, clipping, mapping to viewport.

References relevant to classification in this group
This subclass/group does not cover:
Rasterization
Visualization of models without surface characteristics or attributes
Manipulation and visualization of 3D models for computer graphics
Stereoscopic image generation or displaying
H04N13/00S
Informative references
Attention is drawn to the following places, which may be of interest for search:
Video games
Special rules of classification within this group

The boundaries between G06T 15/00 (in particular G06T 15/08 and G06T 15/10) on the one hand, and G06T 3/0031 and subgroups on the other hand is not yet completely determined. Thus double classification should be considered.

Architectural elements are in general classified in G06T 15/005. However, if the architectural element is only related to a certain part or function within the graphics pipeline (e.g. texture mapping or ray tracing) the document is classified in the respective subgroup (e.g. G06T 15/04 for texture mapping) and additionally the Indexing Code G06T 2200/28 is assigned.

The series G06T 2215/00 of Indexing Codes is reserved for the use of documents classified in G06T 15/00 and subgroups. They should be allocated to documents in G06T 15/00 and subgroups whenever relevant:

Indexing scheme for image rendering: SHOULD BE EMPTY!
curved planar reformation of 3D line structures: CPR of tubular structures (e.g. bronchia, arteries, colon, vertebrae), deployment of line structures in 3D to a 2D plane
gnomonic or central projection: projection from a center of an object, e.g. a ball, to the surrounding surface, related to VTV (virtual television)
shadow map, environment map: generation and use of shadow maps, soft shadows, environment maps
using real world measurements to influence rendering: e.g. shadow based on actual light, viewport based on viewer's pose, texturing with real-time output from camera
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
OpenGL
Open Graphics Library: standard specification defining an application programming interface (API) for writing applications that produce 2D and 3D computer-graphics
Direct3D
standard specification defining an API for writing graphic applications; is part of DirectX
Graphics pipeline
rendering pipeline
Synonyms and Keywords

In patent documents the following expressions/words "rasterization" and "rendering" are often used as synonyms:

{General purpose rendering architectures}
Definition statement
This subclass/group covers:

Functional or operational structure of an image rendering computer system.

Documents in this group focus largely on the way by which the central processing unit (CPU) performs internally with the different units (e.g. the GPU) and accesses memories.

Information relevant is the selection and interconnection of hardware components or functional units in 3D rendering systems.

Hardware and software shader units.

This subgroup is given as classification if the document covers elements of the whole pipeline architecture or if the architectural element covers multiple functions of the graphics pipeline.

References relevant to classification in this group
This subclass/group does not cover:
Architectures for general purpose image data processing
Memory management for general purpose image data processing
Program control in graphics processors
Use of graphics processors for other purposes than rendering
Graphics controllers, e.g. control of visual indicators or display of a graphic pattern
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
GPU
graphics processing unit
Shader unit
instruction sets (in software or hardware) to calculate rendering effects on the graphics hardware
Synonyms and Keywords

In patent documents the following expressions "shader unit" and "hardware shader" are often used as synonyms:

Non-photorealistic rendering
Definition statement
This subclass/group covers:

Means or steps for rendering a scene in a style intended to look like a painting or drawing.

Illustrative examples of non-photorealistic rendering may include, e.g. cartoons, sketches, paintings or drawings.

References relevant to classification in this group
This subclass/group does not cover:
Generation of texture or colour, e.g. brush strokes
Synonyms and Keywords

In patent documents the following expressions "Cartoon-style rendering", "Freehand-style rendering", "Handmade-style rendering", "Ink rendering", "Painterly rendering", "Pen rendering", "Pencil rendering", "Silhouette rendering", "Sketchy rendering", "Toon-Style rendering" and "non-photorealistic rendering" are often used as synonyms.

Texture mapping
Definition statement
This subclass/group covers:

Means or steps for applying or mapping surface detail or colour pattern to a computer-generated graphic, geometry or 3D-model.

Texture mapping used for the generation of a surface image in final format or form is classified herein.

MIP maps, bump mapping, displacement mapping, environment mapping, shadow maps.

References relevant to classification in this group
This subclass/group does not cover:
Generation of texture
Special rules of classification within this group

Documents dealing with shadow maps are classified in both subgroups G06T 15/04 and G06T 15/60.

Documents dealing with environment mapping are classified in both subgroups G06T 15/04 and G06T 15/506.

Documents concerning environment maps or shadow maps are additionally classified with the Indexing Code G06T 2215/12.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Texel
texture element or texture pixel
Ray-tracing
Definition statement
This subclass/group covers:

Means or steps for creating an image by tracing rays from a viewpoint through each pixel to a visible point on an object.

Special rules of classification within this group

Ray casting for hidden part removal is classified in both subgroups G06T 15/06 and G06T 15/40.

Generation of a photon map via photon tracing is classified in both subgroups G06T 15/06 and G06T 15/506.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Ray casting
non-recursive variant of ray tracing
Synonyms and Keywords

In patent documents the following expressions "ray tracing" and "ray casting (especially in early patent documents)" are often used as synonyms:

Volume rendering
Definition statement
This subclass/group covers:

Means or steps for displaying a two-dimensional representation of three-dimensional volume data sets.

Volume data sets are typically voxels or 3D data sets consisting of groups of 2D slice images acquired by e.g. CT, MRT.

Illustrative examples of volume rendering techniques are Direct Volume Rendering Techniques (e.g. splatting, shear warp), Maximum Intensity Projection (MIP), Minimum Intensity Projection, Curved Planar Reformation (CPR), Multiplanar Reformatting (MPR), Curved Multiplanar Reformatting (CMPR).

Technical details of the projection or mapping technique used for volume rendering.

References relevant to classification in this group
This subclass/group does not cover:
Definition of the position of the projection plane, surface or curve for volume rendering
Informative references
Attention is drawn to the following places, which may be of interest for search:
Volumetric displays for the representation of 3D data sets
Special rules of classification within this group

Documents concerning curved planar reformation of tubular structures are additionally classified with the symbol S06T215/04.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
CMPR
Curved Multi-Planar Reformatting
CPR
Curved Planar Reformation
MIP
Maximum (or Minimum) Intensity Projection
MPR
Multi-Planar Reformatting
Synonyms and Keywords

In patent documents the following expressions "curved Planar Reformatting", "curved Multiplanar Reformatting", "curved Multiplanar Reformation", "deployment" and "Curved Planar Reformation" are often used as synonyms.

Geometric effects
Definition statement
This subclass/group covers:

Means or steps for changing the visualization of a graphical object due to view transformations.

Generation of views, multiple views.

Visualization of a graphical object through projection, e.g. parallel projections, oblique projections, gnomonic projections

Mapping of the 3D graphical object on a subspace for visualization, e.g. on (a part of) a plane or on a surface in 3D space (e.g. a bend virtual screen)

References relevant to classification in this group
This subclass/group does not cover:
Visualization of volume data sets
Perspective projections
Changes in the visualization related to lighting effects
Changes in the visualization due to geometric transformations of the object (rotation, translation etc.)
Stereoscopic imaging or 3D displays
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geometric transformations in the plane of the image, i.e. from 2D to 2D
Special rules of classification within this group

The boundaries between G06T 15/10 on the one hand, and G06T 3/005 on the other hand is not yet completely determined. Thus double classification should be considered.

Documents concerning gnomonic or central projections are additionally classified with the Indexing Code G06T 2215/08.

Perspective computation
Definition statement
This subclass/group covers:

Means or steps for presenting a 3D-object on a screen such that objects closer to the viewpoint appear larger than if farther from the viewpoint.

Perspective projections of graphical objects.

Subject matter related to details of viewpoint determination or computation with claimed or disclosed rendering aspects.

References relevant to classification in this group
This subclass/group does not cover:
View determination or computation without rendering
Changing the viewpoint for navigation without details of view generation
Generation of "new perspectives" in stereoscopic imaging, i.e. transformation of stereoscopic image signals corresponding to virtual viewpoints
Informative references
Attention is drawn to the following places, which may be of interest for search:
Navigational Instruments, e.g. visual route guidance with on-board computers using 3D or perspective road maps
Interaction techniques, e.g. control of the viewpoint to navigate in a 3D environment
TV systems, e.g. alteration of picture orientation, perspective, position etc.
Stereoscopic images
Changing parameters of virtual cameras in video games
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Multiple views
rendering a graphical object seen from different viewpoints
View generation
visual rendering of geometric properties of a graphical object seen from a certain viewpoint
Viewpoint alteration
change of a viewpoint (of a virtual camera)
Virtual camera
display of a view of a 3D virtual world
Virtual Studio
technological tools for simulating a physical television or movie studio, the image of the virtual camera is rendered in real-time from the same perspective as the real camera in 3D space
{Image-based rendering}
Definition statement
This subclass/group covers:

Means or steps for rendering a 3D-object or scene using a set of two-dimensional images of it.

Generation of a new view of a graphics object exclusively from 2D images of the object without prior generation of a 3D model.

Rendering using billboards.

Pixel based rendering or point based rendering of 3D objects which are not volume data.

Depth image-based rendering.

References relevant to classification in this group
This subclass/group does not cover:
Analysis of image-based rendering pictures or calculation of disparity values from multiple images for IBR
Calculation of depth values from multiple images
Splatting of volume data
Rendering of a 3D model generated from 2D images of it
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
IBR
image-based rendering
Billboard
textured rectangles that are used as simplified version of 3D models for rendering
Clipping
Definition statement
This subclass/group covers:

Means or steps for eliminating those portions of graphics primitives that extend beyond a predetermined region.

The predetermined region may include a viewing volume or any subset of the view volume of any shape.

The shape of the graphics primitives that partly extend beyond the predetermined region is modified.

References relevant to classification in this group
This subclass/group does not cover:
Cropping of 2D images
Special rules of classification within this group

Documents where a bounding box or shape is defined or used are additionally classified with the Indexing Code G06T 2210/12.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Bounding box or bounding shape
minimal box or convex polygon surrounding the graphic object
Viewport
rectangular area on the screen for displaying the rendered graphical object
Synonyms and Keywords

In patent documents the following expressions "viewing volume", "view volume" and "view frustum" are often used as synonyms.

Hidden part removal
Definition statement
This subclass/group covers:

Means or steps for determining which surfaces or part of surfaces of a graphic object are visible from a certain viewpoint and optionally removing them.

Hidden surface or line removal.

Culling, e.g. frustum culling, backface culling, frontface culling, occlusion culling. Culling removes graphics objects or scene graph nodes that are completely falling outside the view frustum. This is usually performed before clipping.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
VSD
visible surface determination
{using Z-buffer}
Definition statement
This subclass/group covers:

Means or steps for determining which surfaces or parts of surfaces of a graphic object are visible from a certain viewpoint and optionally removing them using Z-Buffer information.

Synonyms and Keywords

In patent documents the following expressions "Z-Buffer" and "Depth-Buffer" are often used as synonyms:

Lighting effects
Definition statement
This subclass/group covers:

Means or steps for determining intensity or colour on a surface of an object based on interaction of light with the object, considering surface properties or its orientation.

{Blending, e.g. for anti-aliasing}
Definition statement
This subclass/group covers:

Means or steps for computing an image or pixel-value form several (source) images or pixel-values taking into account their weighting factors.

Weighting factors are usually opacity or transparency associated values.

Compositing.

Vertex or geometry blending.

References relevant to classification in this group
This subclass/group does not cover:
Video editing or indexing or timing
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Alpha channel or alpha transparency channel
a portion of each pixel's data that is reserved for transparency information
Alpha compositing
combining an image with a background to create the appearance of partial or full transparency
Matte
contains the coverage information, e.g. the shape of the object to be drawn
{Illumination models}
Definition statement
This subclass/group covers:

Means or steps for computing the amount of energy absorbed, reflected, diffracted or transmitted by an object (or element) to be 3D rendered.

Illumination models usually include composition, direction or geometry of the light source, surface orientation and/or surface properties of the object.

Local illumination models only take into account light arriving straight from the light source.

Global illumination models take into account light arriving after interaction with another object in the scene.

Direct light sources, indirect light sources, multiple light sources, physically based illumination models.

Special rules of classification within this group

Generation of a photon map via photon tracing is classified in both subgroups G06T 15/06 and G06T 15/506.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
BRDF
bidirectional reflectance distribution function
Radiosity
Definition statement
This subclass/group covers:

Means or steps for rendering graphic objects through computing the balancing of substantially all light energy coming toward and going away from every point on a surface.

In radiosity, the balance of light energy is usually independent of the viewpoint.

References relevant to classification in this group
This subclass/group does not cover:
Subject matter directed to illumination models that only consider viewpoint dependent vectors
Shadow generation
Definition statement
This subclass/group covers:

Means or steps for determination and generation of a region of darkness on an object where light is at least partially blocked by another graphical object.

The blocking object herein might be a semitransparent object.

Shadow computation normally refers to computation of shadow caused by one object onto another object.

Concave Objects where the shadow caused by one portion of the object falls onto another portion of the concave object is classified herein, e.g. an “L” shaped object can cast a shadow from the vertical portion onto the horizontal portion.

Special rules of classification within this group

Documents concerning the calculation of the position of the light source from the shadow are classified in both subgroups G06T 15/50 and G06T 15/60.

Documents concerning shadow maps are classified in both subgroups G06T 15/04 and G06T 15/60 and are additionally classified with the Indexing Code G06T 2215/12.

Shading
Definition statement
This subclass/group covers:

Means or steps for assigning colour or intensity alterations or gradations in a particular area of a graphical object’s surface based on its relationship with light.

Relationship of light herein includes vector of light which consists of angle and distance or it even may include ambient light.

Surfaces may include polygons or curved surfaces or patches.

Interpolation of colour or shade based on vertex data or other pixels on the surface is classified herein.

Shading caused by the object blocking light on the back side of the same object with respect to a light source is classified herein.

References relevant to classification in this group
This subclass/group does not cover:
Shader units
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Scanline interpolation
Interpolation of values along each surface edge linearly and interpolatation of values in the interior of each surface from left edge to rightedge, i.e. along a scanline
Phong shading
Definition statement
This subclass/group covers:

Means or steps for interpolating surface normals from the vertices of a graphical object in rasterizing a surface thereby calculating specular reflections on a graphical object.

Gouraud shading
Definition statement
This subclass/group covers:

Means or steps for producing a smooth variation of surface intensity over a surface by bilinearly interpolating the color or intensities from the vertices of a graphical object.

Three dimensional [3D] modelling, e.g. data description of 3D objects
Definition statement
This subclass/group covers:

Means or steps for generating a description of a 3D model or scene.

The 3D model description is usually generated from point clouds, 2D images, mathematical definitions for the description of curves, surfaces or volumes or data from different sensors.

Marching Cubes, sampled distance fields.

Image data format conversions, e.g. converting polar coordinates to rectangular coordinates or IGES to combinatorial geometry descriptions.

References relevant to classification in this group
This subclass/group does not cover:
Route guidance using 3D or perspective road maps including 3D objects and buildings
Generation of 3D objects with NC-machines
CAM (Computer aided manufacturing)
CAD (Computer aided design) in general
Manipulating 3D models or images for computer graphics
Depth or shape recovery from the analysis of 2D images
Stereo image generation
Informative references
Attention is drawn to the following places, which may be of interest for search:
Methods for drafting or marking-out cutting-out patterns for cloth
Collision detection for path planning of manipulators
Collision detection for programme-controlled systems
Stereo image generation
Special rules of classification within this group

Documents concerning image data format conversion are additionally classified with the Indexing Code G06T 2210/32 - image data format.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
IGES
Initial Graphics Exchange Specification
{Tree description, e.g. octree, quadtree}
Definition statement
This subclass/group covers:

Means or steps for generating a hierarchical tree-based description of a 3D model or scene.

Special rules of classification within this group

Documents concerning scene graphs are additionally classified with the Indexing Code G06T 2210/61 - scene description

Synonyms and Keywords

In patent documents the following expressions are often used as synonyms:

"Bintree or binary tree" and "tree structure in which each node has at most two child nodes"

"Quadtree or quad tree" and "tree structure in which each node has at most four child nodes"

"K-tree" and "tree structure in which each node has at most K child nodes"

"Hextree" and "tree structure in which each node has at most six child nodes"

"Volume octree" and "tree structure in which each voxel is subdivided into at most 8 subvoxels"

"Surface octree" and "Volume octree with incorporated surface information"

"Multi tree" and "directed acyclic graph in which the set of nodes reachable from any node forms a tree"

Geographic models
Definition statement
This subclass/group covers:

Means or steps for generating 3D models which relate to geographic data.

The geographic data is usually obtained from different sensors, e.g. LIDAR, stereo photogrammetry from aerial surveys, radar, infrared cameras, GPS, satellite photography and maps e.g. topographic maps, road maps, development plans.

Digital Elevation Models (DEM), contour maps, digital cartography.

Superimposing or overlaying of registered geographic data from different sensors.

Editing of maps, e.g. modelling of roofs or generation of 3D models for buildings displayed on a map.

Map revision, map updating.

Calculation of visibility fields for geographic areas.

Geographical fractal modeling.

References relevant to classification in this group
This subclass/group does not cover:
Navigation in a road network, GPS for navigation
Navigational Instruments, e.g. visual route guidance using 3D or perspective road maps (including 3D objects and buildings)
Registration of 2D images from different sensors
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geometric image transformations for image registration
Special rules of classification within this group

This subgroup is an application oriented group. Therefore, whenever possible, documents classified herein should also be classified in a function oriented group.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
GIS
Geographic Information Systems
AMS
Automated Mapping System
Synonyms and Keywords

In patent documents the following expressions are often used as synonyms:

Chorography
description of a landscape
Choropleth map
thematic map
Constructive solid geometry (CSG) using solid primitives, e.g. cylinders, cubes
Definition statement
This subclass/group covers:

Means or steps for generating 3D models using boundary or volumetric representations of solid primitive objects.

Incremental feature generation, feature modification or modelling, feature-based design is classified here.

Solid modelling via sheet modelling or via sweeping or extrusion of contours, areas or volumes, e.g. the generation of sweep objects or generalized cylinders.

Modelling of solids using volumetric representations, an "alternating sum of volumes" process, volume or convex decomposition or boundary representations.

Generation of 3D objects from 2D line drawings.

Special rules of classification within this group

For specific aspects of documents In this group the following additional Indexing Codes from the series G06T 2210/00 should be allocated whenever relevant:

For convex hull for 3D objects: G06T 2210/12

For collision detection or intersection of 3D objects: G06T 2210/21

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
B-rep or BREP
boundary representation
Alternating sum of volumes (ASV) process
a convex decomposition method for volumetric objects
Synonyms and Keywords

In patent documents the following expressions "sweep object" and "generalized cylinder" are often used as synonyms.

Finite element generation, e.g. wire-frame surface description, {tesselation}
Definition statement
This subclass/group covers:

Means or steps for the generation or modification of polygonal surface descriptions of 3D models or parts thereof.

Meshes, grids, tessellations, tessellated surface patches, triangulations, tilings are classified here.

Delaunay triangulation, Voronoi diagrams.

Concatenation of tessellated surface patches, T-junctions.

Meshes for finite element modelling.

References relevant to classification in this group
This subclass/group does not cover:
Compression using wireframes
Computer-aided design using finite element methods
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geologic models
Seismic models
Special rules of classification within this group

For specific aspects of documents In this group the following additional Indexing Codes from the series G06T 2210/00 should be allocated whenever relevant:

For modelling of cloth: G06T 2210/16

For collision detection or intersection of 3D objects: G06T 2210/21

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
FEM
Finite element modelling
TIN
Triangulated irregular network
T-junction
a spot where two polygons meet along the edge of another polygon
{Re-meshing}
Definition statement
This subclass/group covers:

Means or steps for modifying the structure of a mesh by inserting or deleting mesh vertices.

Generation of meshes with different level of detail from a source mesh.

Refinement or simplification of meshes, honeycomb scheme.

The refinement or coarsening may be locally or globally.

Special rules of classification within this group

Documents concerning the generation of meshes with different levels of detail are additionally classified with the Indexing Code G06T 2210/36.

Polynomial surface description
Definition statement
This subclass/group covers:

Means or steps for generating a meshfree surface description.

Polynomial surface descriptions, e.g. NURBS, Bézier surfaces, B-spline surfaces, Coons patches, Tensor product patches, without mesh generation or visualization based on tessellations.

Analytical surface descriptions.

Free-form surfaces.

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
NURBS
Non-Uniform Rational B-Spline
Manipulating 3D models or images for computer graphics
Definition statement
This subclass/group covers:

Means or steps for changing 3D models, for adding information or for changing the visualization via a user interface.

View determination or computation without rendering details, geometric transformations of the whole 3D object to change the viewpoint.

Manipulating 3D models by multiple users in a collaborative environment.

Annotating or labelling of 3D models with text, markers

Dimensioning and tolerancing of 3D models, e.g. display of dimension information for each part

Display of 3D models as an exploded view drawing.

Unfolding or flattening of 3D models or graphs.

Positioning or defining a cut plane or a curved surface in a 3D volume data set, e.g. for projection in volume rendering.

Manipulating 3D data while displaying or updating several views at the same time, e.g. top, front, and side view or sagittal, coronal, and axial view for medical applications.

Virtual try-on or virtual 3D design systems, e.g. virtual dressing or fitting-rooms, virtual mannequins, virtual interior or garden design, architectural design, virtual car configurators.

For documents in this group the function of manipulating 3D objects is prevailing, not the details how it is achieved. Therefore, the documents are usually general and do not contain specific technical details, e.g. documents concerning the change of the viewpoint via a GUI are classified here whereas documents with mathematical details on the change of the viewpoint and the frustum are classified in G06T 15/20.

References relevant to classification in this group
This subclass/group does not cover:
CAD-CAM (Computer Aided Design and Manufacturing)
Generation of 3D objects with NC-machines
Interaction techniques for graphical user interfaces
Informative references
Attention is drawn to the following places, which may be of interest for search:
Video games
Computer-aided design
2D cosmetic or hairstyle simulations
Viewpoint transformation of stereoscopic image signals
Special rules of classification within this group

The boundaries between G06T 19/00 on the one hand, and G06T 3/0031 and subgroups and G06T 3/005 on the other hand is not yet completely determined. Thus double classification should be considered.

The Indexing Code series G06T 2219/00 and below is reserved for documents classified in G06T 19/00 and subgroups. They should be allocated to documents in G06T 19/00 whenever relevant:

Indexing scheme for manipulating 3D models or images for computer graphics: SHOULD BE EMPTY!
annotating, labelling: annotating or labelling of 3D models or 3D images with text or markers
cut plane or projection plane definition: positioning or defining a cut plane or a curved surface in a 3D volume data set, e.g. for projection in volume rendering
dimensioning, tolerancing: dimensioning or tolerancing of 3D models, e.g. display of dimension information for each part of the model
exploded view: displaying 3D models as an exploded view drawing
flattening: unfolding or flattening of 3D models or graphs in a 2D plane
multi-user, collaborative environment: collaborative environments, multi-user environments
multiple view windows (top-side-front-sagittal-orthogonal): manipulating 3D data while displaying or updating several views at the same time, e.g. sagittal, axial, and coronal view or top, side, and front view

The Indexing Code series G06T 2219/20 and below is reserved exclusively for documents classified in G06T 19/20. To each document classified in G06T 19/20 at least one of the symbols from this series should be allocated:

Indexing scheme for editing of 3D models: SHOULD BE EMPTY!
aligning objects, relative positioning of parts: aligning graphical objects or relative positioning of parts of a 3D model
assembling, disassembling: assembling and disassembling of parts of a 3D model
colour coding, editing, changing, or manipulating: colour modifications, e.g. colour coding, use of pseudo-colour, highlighting object parts in a different colour
rotation, translation, scaling: Euclidian transformations of the object or parts thereof, i.e. rotation, translation/dragging/shifting, reflection/mirroring, or size changes of a 3D object or parts thereof
shape modification: shape modifications of a 3D object, e.g. adding or deleting parts of the object, shearing, free-form deformations
style variation: modifications of the display style, e.g. changes of patterns for surfaces, change of line drawing style (e.g. bold lines, dotted lines), displaying more details of an object or of parts thereof in a separate window

Furthermore, symbols from the Indexing Code series G06T 2200/00 and below as well as G06T 2210/00 and below should be allocated to documents in G06T 19/00 and subgroups whenever relevant.

For the documents in the group G06T 19/00 the following additional symbols from the Indexing Code series G06T 2210/00 and below are especially relevant and should be allocated whenever possible:

For architectural design: G06T 2210/04

For bandwidth reduction: G06T 2210/08

Convex hull for 3D objects: G06T 2210/12

For virtual dressing rooms: G06T 2210/16

For collision detection of 3D objects: G06T 2210/21

For medical applications concerning e.g. heart, lung, brain, tumours: G06T 2210/41

{Navigation within 3D models or images}
Definition statement
This subclass/group covers:

Means or steps for generating a sequence of images of a virtual movement (e.g. flight, walk, sail) through a 3D space or scene.

Navigation path or flight path determination.

Virtual navigation within human or animal bodies or organs, e.g. virtual medical endoscopy of the colon, of the ventricular system, of the vascular system, of the bronchial tree, or within 3D objects, e.g. virtual inspection of pipeline tubes.

Walk- or flight-through a virtual museum, a virtual building, a virtual landscape etc.

References relevant to classification in this group
This subclass/group does not cover:
Navigational instruments, e.g. visual route guidance using 3D or perspective road maps (including 3D objects and buildings)
Interaction techniques for GUIs, e.g. control of the viewpoint to navigate in a 3D environment
Informative references
Attention is drawn to the following places, which may be of interest for search:
Centreline determination
3D animation
Virtual racing games
Surgical planning
Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
Virtual angioscopy
virtual endoscopy of the vascular system
Virtual bronchoscopy
virtual endoscopy of the bronchial tree
Virtual colonoscopy
virtual endoscopy of the colon
Virtual ventriculoscopy
virtual endoscopy of the ventricular system
Synonyms and Keywords

In patent documents the following expressions "virtual fly through navigation", "virtual navigation", "virtual flight", "virtual fly-through" and "virtual walk-through" are often used as synonyms.

{Mixed reality ( object pose determination, tracking or camera calibration for mixed reality G06T 7/00) }
Definition statement
This subclass/group covers:

Means or steps for generating 3D mixed reality, i.e. displaying 3D virtual model data together with 2D or 3D real-world image data or for displaying 2D virtual model data together with 3D real-world image data, e.g. real volume data.

3D mixed reality encompasses 3D augmented reality and 3D augmented virtuality.

References relevant to classification in this group
This subclass/group does not cover:
Object pose determination, tracking or camera calibration for mixed reality
Mixed reality by combining 2D virtual models or text with 2D real image data
Informative references
Attention is drawn to the following places, which may be of interest for search:
Head-up displays, head mounted displays
Helmet-mounted display of stereo images
Volumetric displays, e.g. for display of mixed reality scenes
Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
Definition statement
This subclass/group covers:

Means or steps for changing the visual appearance of the 3D object or parts thereof or for changing the position of the 3D object or parts thereof in the visualization environment.

Shape modifications of the 3D object, e.g. adding or deleting parts of the 3D object, shearing, free-form deformations.

Colour modifications, e.g. colour coding, use of pseudo-colour, highlighting object parts in a different colour.

Modifications of the display style, e.g. changes of patterns for surfaces, change of line drawing style (e.g. stroke width and pattern), displaying more details of the object or of parts thereof in a separate window).

Shifting objects or parts thereof, aligning objects, rotating parts of the object or model, Euclidian transformations, size changes of the object or parts thereof.

Assembling and disassembling of object parts, connecting or mating different 3D parts.

References relevant to classification in this group
This subclass/group does not cover:
Geometric transformations of the whole 3D object to change the viewpoint but without rendering details
Informative references
Attention is drawn to the following places, which may be of interest for search:
Geometric image transforms in the image plane
Colour changes in 2D images
Editing of 2D images
Time-related zooming on 3D objects
Time-related zooming on 2D images
Special rules of classification within this group

For the documents in the group G06T 19/00 the following additional symbols from the Indexing Code series G06T 2210/00 and below are especially relevant. To each document classified in G06T 19/20 at least one of the following symbols should be allocated:

For aligning objects, relative positioning of parts: G06T 2219/2004

For assembling, disassembling: G06T 2219/2008

For colour coding, editing, changing, or manipulating, pseudo-colours, highlighting: G06T 2219/2012

For rotation, translation, scaling: G06T 2219/2016

For shape modifications, adding or deleting parts, shearing, free form deformations: G06T 2219/2021

For modifications of the display style, e.g. changes of patterns for surfaces, change of line drawing style: G06T 2219/2024

Glossary of terms
In this subclass/group, the following terms (or expressions) are used with the meaning indicated:
DDM
Direct deformation method
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Last Modified: 10/11/2013