Version: 2025.01
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CPC | COOPERATIVE PATENT CLASSIFICATION | |||
| G06V | IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING [2023-08] NOTES
|
G06V 10/00 | Arrangements for image or video recognition or understanding (character recognition in images or video G06V 30/10) [2023-08] |
G06V 10/10 | . | Image acquisition (document image scanning and transmission H04N 1/00; control of digital cameras H04N 23/60) [2023-08] |
G06V 10/12 | . . | Details of acquisition arrangements; Constructional details thereof [2023-08] |
G06V 10/14 | . . . | Optical characteristics of the device performing the acquisition or on the illumination arrangements [2023-08] |
G06V 10/141 | . . . . | Control of illumination [2023-08] |
G06V 10/143 | . . . . | Sensing or illuminating at different wavelengths [2023-08] |
G06V 10/145 | . . . . | Illumination specially adapted for pattern recognition, e.g. using gratings [2023-08] |
G06V 10/147 | . . . . | Details of sensors, e.g. sensor lenses (fingerprint or palmprint sensors G06V 40/13; vascular sensors G06V 40/145; eye sensors G06V 40/19) [2023-08] |
G06V 10/16 | . . | {using multiple overlapping images; Image stitching} [2023-08] |
G06V 10/17 | . . | {using hand-held instruments} [2023-08] |
G06V 10/19 | . . | {by sensing codes defining pattern positions} [2023-08] |
G06V 10/20 | . | Image preprocessing [2023-08] |
G06V 10/22 | . . | by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition [2023-08] |
G06V 10/225 | . . . | {based on a marking or identifier characterising the area} [2023-08] |
G06V 10/23 | . . . | {based on positionally close patterns or neighbourhood relationships} [2023-08] |
G06V 10/235 | . . . | {based on user input or interaction} [2023-08] |
G06V 10/24 | . . | Aligning, centring, orientation detection or correction of the image [2023-08] |
G06V 10/242 | . . . | {by image rotation, e.g. by 90 degrees} [2023-08] |
G06V 10/243 | . . . | {by compensating for image skew or non-uniform image deformations} [2023-08] |
G06V 10/245 | . . . | {by locating a pattern; Special marks for positioning} [2023-08] |
G06V 10/247 | . . . | {by affine transforms, e.g. correction due to perspective effects; Quadrilaterals, e.g. trapezoids} [2023-08] |
G06V 10/248 | . . . | {by interactive preprocessing or interactive shape modelling, e.g. feature points assigned by a user} [2023-08] |
G06V 10/25 | . . | Determination of region of interest [ROI] or a volume of interest [VOI] [2023-08] |
G06V 10/255 | . . | {Detecting or recognising potential candidate objects based on visual cues, e.g. shapes} [2023-08] |
G06V 10/26 | . . | Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion [2023-08] |
G06V 10/267 | . . . | {by performing operations on regions, e.g. growing, shrinking or watersheds} [2023-08] |
G06V 10/273 | . . . | {removing elements interfering with the pattern to be recognised} [2023-08] |
G06V 10/28 | . . | Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns [2023-08] |
G06V 10/30 | . . | Noise filtering [2023-08] |
G06V 10/32 | . . | Normalisation of the pattern dimensions [2023-08] |
G06V 10/34 | . . | Smoothing or thinning of the pattern; Morphological operations; Skeletonisation [2023-08] |
G06V 10/36 | . . | Applying a local operator, i.e. means to operate on image points situated in the vicinity of a given point; Non-linear local filtering operations, e.g. median filtering [2023-08] |
G06V 10/40 | . | Extraction of image or video features [2023-08] |
G06V 10/42 | . . | Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation [2023-08] |
G06V 10/421 | . . . | {by analysing segments intersecting the pattern} [2023-08] |
G06V 10/422 | . . . | for representing the structure of the pattern or shape of an object therefor [2023-08] |
G06V 10/424 | . . . . | Syntactic representation, e.g. by using alphabets or grammars [2023-08] |
G06V 10/426 | . . . . | Graphical representations [2023-08] |
G06V 10/431 | . . . | {Frequency domain transformation; Autocorrelation} [2023-08] |
G06V 10/435 | . . . | {Computation of moments} [2023-08] |
G06V 10/44 | . . | Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components [2023-08] |
G06V 10/443 | . . . | {by matching or filtering} [2023-08] |
G06V 10/446 | . . . . | {using Haar-like filters, e.g. using integral image techniques} [2023-08] |
G06V 10/449 | . . . . | {Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters} [2023-08] |
G06V 10/451 | . . . . . | {with interaction between the filter responses, e.g. cortical complex cells} [2023-08] |
G06V 10/454 | . . . . . . | {Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]} [2023-08] |
G06V 10/457 | . . . | {by analysing connectivity, e.g. edge linking, connected component analysis or slices} [2023-08] |
G06V 10/46 | . . | Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features (colour feature extraction G06V 10/56) [2023-08] |
G06V 10/462 | . . . | {Salient features, e.g. scale invariant feature transforms [SIFT]} [2023-08] |
G06V 10/464 | . . . . | {using a plurality of salient features, e.g. bag-of-words [BoW] representations} [2023-08] |
G06V 10/467 | . . . | {Encoded features or binary features, e.g. local binary patterns [LBP]} [2023-08] |
G06V 10/469 | . . . | {Contour-based spatial representations, e.g. vector-coding} [2023-08] |
G06V 10/471 | . . . . | {using approximation functions} [2023-08] |
G06V 10/473 | . . . . | {using gradient analysis} [2023-08] |
G06V 10/476 | . . . . | {using statistical shape modelling, e.g. point distribution models} [2023-08] |
G06V 10/478 | . . . | {Contour-based spectral representations or scale-space representations, e.g. by Fourier analysis, wavelet analysis or curvature scale-space [CSS]} [2023-08] |
G06V 10/48 | . . | by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation [2023-08] |
G06V 10/50 | . . | by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis [2023-08] |
G06V 10/507 | . . . | {Summing image-intensity values; Histogram projection analysis} [2023-08] |
G06V 10/513 | . . | {Sparse representations} [2023-08] |
G06V 10/52 | . . | Scale-space analysis, e.g. wavelet analysis (multi-scale boundary representations G06V 10/42) [2023-08] |
G06V 10/54 | . . | relating to texture [2023-08] |
G06V 10/56 | . . | relating to colour [2023-08] |
G06V 10/58 | . . | relating to hyperspectral data [2023-08] |
G06V 10/60 | . . | relating to illumination properties, e.g. using a reflectance or lighting model [2023-08] |
G06V 10/62 | . . | relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking [2023-08] |
G06V 10/70 | . | using pattern recognition or machine learning (optical pattern recognition or electronic computations therefor G06V 10/88) [2023-08] |
G06V 10/72 | . . | Data preparation, e.g. statistical preprocessing of image or video features [2023-08] |
G06V 10/74 | . . | Image or video pattern matching; Proximity measures in feature spaces [2022-01] |
G06V 10/75 | . . . | Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries [2023-08] |
G06V 10/751 | . . . . | {Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching} [2023-08] |
G06V 10/7515 | . . . . . | {Shifting the patterns to accommodate for positional errors} [2023-08] |
G06V 10/752 | . . . . | {Contour matching} [2023-08] |
G06V 10/753 | . . . . | {Transform-based matching, e.g. Hough transform} [2023-08] |
G06V 10/754 | . . . . | {involving a deformation of the sample pattern or of the reference pattern; Elastic matching} [2023-08] |
G06V 10/755 | . . . . | {Deformable models or variational models, e.g. snakes or active contours} [2023-08] |
G06V 10/7553 | . . . . . | {based on shape, e.g. active shape models [ASM]} [2023-08] |
G06V 10/7557 | . . . . . | {based on appearance, e.g. active appearance models [AAM]} [2023-08] |
G06V 10/757 | . . . . | {Matching configurations of points or features} [2023-08] |
G06V 10/758 | . . . . | {Involving statistics of pixels or of feature values, e.g. histogram matching} [2023-08] |
G06V 10/759 | . . . . | {Region-based matching} [2023-08] |
G06V 10/76 | . . . . | {based on eigen-space representations, e.g. from pose or different illumination conditions; Shape manifolds} [2023-08] |
G06V 10/761 | . . . | {Proximity, similarity or dissimilarity measures} [2023-08] |
G06V 10/762 | . . | using clustering, e.g. of similar faces in social networks [2023-08] |
G06V 10/7625 | . . . | {Hierarchical techniques, i.e. dividing or merging patterns to obtain a tree-like representation; Dendograms} [2023-08] |
G06V 10/763 | . . . | {Non-hierarchical techniques, e.g. based on statistics of modelling distributions} [2023-08] |
G06V 10/7635 | . . . | {based on graphs, e.g. graph cuts or spectral clustering} [2023-08] |
G06V 10/764 | . . | using classification, e.g. of video objects [2023-08] |
G06V 10/765 | . . . | {using rules for classification or partitioning the feature space} [2023-08] |
G06V 10/766 | . . | using regression, e.g. by projecting features on hyperplanes [2022-01] |
G06V 10/768 | . . | {using context analysis, e.g. recognition aided by known co-occurring patterns} [2023-08] |
G06V 10/771 | . . . | Feature selection, e.g. selecting representative features from a multi-dimensional feature space [2023-08] |
G06V 10/7715 | . . . | {Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods} [2023-08] |
G06V 10/772 | . . . | Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries [2023-08] |
G06V 10/774 | . . . | Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting [2023-08] |
G06V 10/7747 | . . . . | {Organisation of the process, e.g. bagging or boosting} [2023-08] |
G06V 10/7753 | . . . . | {Incorporation of unlabelled data, e.g. multiple instance learning [MIL]} [2023-08] |
G06V 10/776 | . . . | Validation; Performance evaluation [2023-08] |
G06V 10/778 | . . . | Active pattern-learning, e.g. online learning of image or video features [2023-08] |
G06V 10/7784 | . . . . | {based on feedback from supervisors} [2023-08] |
G06V 10/7788 | . . . . . | {the supervisor being a human, e.g. interactive learning with a human teacher} [2023-08] |
G06V 10/7792 | . . . . . | {the supervisor being an automated module, e.g. "intelligent oracle"} [2022-01] |
G06V 10/7796 | . . . . | {based on specific statistical tests} [2023-08] |
G06V 10/80 | . . . | Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level (multimodal speaker identification or verification G10L 17/10) [2023-08] |
G06V 10/803 | . . . . | {of input or preprocessed data} [2023-08] |
G06V 10/806 | . . . . | {of extracted features} [2023-08] |
G06V 10/809 | . . . . | {of classification results, e.g. where the classifiers operate on the same input data} [2023-08] |
G06V 10/811 | . . . . . | {the classifiers operating on different input data, e.g. multi-modal recognition} [2023-08] |
G06V 10/814 | . . . . | {using belief theory, e.g. Dempster-Shafer} [2023-08] |
G06V 10/817 | . . . . | {by voting} [2023-08] |
G06V 10/82 | . . | using neural networks [2022-01] |
G06V 10/84 | . . | using probabilistic graphical models from image or video features, e.g. Markov models or Bayesian networks [2023-08] |
G06V 10/85 | . . . | {Markov-related models; Markov random fields} [2023-08] |
G06V 10/86 | . . | using syntactic or structural representations of the image or video pattern, e.g. symbolic string recognition; using graph matching [2022-01] |
G06V 10/87 | . . | {using selection of the recognition techniques, e.g. of a classifier in a multiple classifier system} [2023-08] |
G06V 10/88 | . | Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters [2023-08] |
G06V 10/89 | . . | {using frequency domain filters, e.g. Fourier masks implemented on spatial light modulators} [2023-08] |
G06V 10/893 | . . . | {characterised by the kind of filter} [2023-08] |
G06V 10/895 | . . . . | {the filter being related to phase processing, e.g. phase-only filters} [2023-08] |
G06V 10/898 | . . . . | {combination of filters, e.g. phase-only filters} [2023-08] |
G06V 10/92 | . . | {using spatial domain filters, e.g. joint transform correlators} [2023-08] |
G06V 10/94 | . | Hardware or software architectures specially adapted for image or video understanding [2023-08] |
G06V 10/945 | . . | {User interactive design; Environments; Toolboxes} [2023-08] |
G06V 10/95 | . . | {structured as a network, e.g. client-server architectures} [2022-01] |
G06V 10/955 | . . | {using specific electronic processors} [2022-01] |
G06V 10/96 | . | Management of image or video recognition tasks [2023-08] |
G06V 10/98 | . | Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns [2023-08] |
G06V 10/987 | . . | {with the intervention of an operator} [2023-08] |
G06V 10/993 | . . | {Evaluation of the quality of the acquired pattern} [2023-08] |
G06V 20/05 | . | Underwater scenes [2023-08] |
G06V 20/10 | . | Terrestrial scenes (scenes under surveillance with static cameras G06V 20/52; scenes perceived from the exterior of a vehicle G06V 20/56; scenes perceived from the interior of a vehicle G06V 20/59) [2023-08] |
G06V 20/13 | . . | Satellite images [2023-08] |
G06V 20/17 | . . | taken from planes or by drones [2023-08] |
G06V 20/176 | . . | {Urban or other man-made structures} [2022-01] |
G06V 20/182 | . . | {Network patterns, e.g. roads or rivers} [2022-01] |
G06V 20/188 | . . | {Vegetation} [2022-01] |
G06V 20/194 | . . | {using hyperspectral data, i.e. more or other wavelengths than RGB} [2022-01] |
G06V 20/20 | . | in augmented reality scenes [2023-08] |
G06V 20/30 | . | in albums, collections or shared content, e.g. social network photos or video [2023-08] |
G06V 20/35 | . | {Categorising the entire scene, e.g. birthday party or wedding scene} [2023-08] |
G06V 20/36 | . . | {Indoor scenes} [2022-01] |
G06V 20/38 | . . | {Outdoor scenes} [2022-01] |
G06V 20/39 | . . . | {Urban scenes} [2022-01] |
G06V 20/40 | . | in video content (extracting overlay text G06V 20/62; video retrieval G06F 16/70; processing of video elementary streams in video servers H04N 21/234; processing of video elementary streams in video clients H04N 21/44) [2023-08] |
G06V 20/41 | . . | {Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items (segmenting video sequences G06V 20/49)} [2022-01] |
G06V 20/42 | . . . | {of sport video content} [2022-01] |
G06V 20/43 | . . . | {of news video content} [2022-01] |
G06V 20/44 | . . | {Event detection} [2022-01] |
G06V 20/46 | . . | {Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames} [2022-01] |
G06V 20/47 | . . . | {Detecting features for summarising video content} [2022-01] |
G06V 20/48 | . . | {Matching video sequences} [2022-01] |
G06V 20/49 | . . | {Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes} [2022-01] |
G06V 20/50 | . | Context or environment of the image [2023-08] |
G06V 20/52 | . . | Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V 20/69) [2023-08] |
G06V 20/53 | . . . | {Recognition of crowd images, e.g. recognition of crowd congestion} [2022-01] |
G06V 20/54 | . . . | of traffic, e.g. cars on the road, trains or boats [2022-01] |
G06V 20/56 | . . | exterior to a vehicle by using sensors mounted on the vehicle [2023-08] |
G06V 20/58 | . . . | Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads [2022-01] |
G06V 20/582 | . . . . | {of traffic signs} [2022-01] |
G06V 20/584 | . . . . | {of vehicle lights or traffic lights} [2022-01] |
G06V 20/586 | . . . . | {of parking space} [2022-01] |
G06V 20/588 | . . . | {Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road} [2022-01] |
G06V 20/59 | . . | inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions [2023-08] |
G06V 20/593 | . . . | {Recognising seat occupancy} [2022-01] |
G06V 20/597 | . . . | {Recognising the driver's state or behaviour, e.g. attention or drowsiness} [2022-01] |
G06V 20/60 | . | Type of objects [2023-08] |
G06V 20/62 | . . | Text, e.g. of license plates, overlay texts or captions on TV images [2023-08] |
G06V 20/625 | . . . | {License plates} [2022-01] |
G06V 20/63 | . . . | {Scene text, e.g. street names} [2022-01] |
G06V 20/635 | . . . | {Overlay text, e.g. embedded captions in a TV program} [2022-01] |
G06V 20/64 | . . | Three-dimensional objects [2023-08] |
G06V 20/647 | . . . | {by matching two-dimensional images to three-dimensional objects} [2022-01] |
G06V 20/653 | . . . | {by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces} [2022-01] |
G06V 20/66 | . . | Trinkets, e.g. shirt buttons or jewellery items (recognising microscopic objects G06V 20/69) [2022-01] |
G06V 20/68 | . . | Food, e.g. fruit or vegetables [2023-08] |
G06V 20/69 | . . | Microscopic objects, e.g. biological cells or cellular parts [2022-01] |
G06V 20/693 | . . . | {Acquisition} [2022-01] |
G06V 20/695 | . . . | {Preprocessing, e.g. image segmentation} [2022-01] |
G06V 20/698 | . . . | {Matching; Classification} [2022-01] |
G06V 20/70 | . | Labelling scene content, e.g. deriving syntactic or semantic representations [2023-08] |
G06V 20/80 | . | Recognising image objects characterised by unique random patterns [2023-08] |
G06V 20/90 | . | Identifying an image sensor based on its output data [2023-08] |
G06V 20/95 | . | {Pattern authentication; Markers therefor; Forgery detection} [2022-01] |
| G06V 30/00 | Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition (scanning, transmission or reproduction of documents or the like H04N 1/00) [2023-08] NOTE
|
G06V 30/10 | . | Character recognition [2023-08] |
G06V 30/12 | . . | Detection or correction of errors, e.g. by rescanning the pattern [2023-08] |
G06V 30/127 | . . . | {with the intervention of an operator} [2023-08] |
G06V 30/133 | . . . | {Evaluation of quality of the acquired characters} [2023-08] |
G06V 30/14 | . . | Image acquisition [2023-08] |
G06V 30/141 | . . . | {using multiple overlapping images; Image stitching} [2023-08] |
G06V 30/142 | . . . | using hand-held instruments; Constructional details of the instruments [2023-08] |
G06V 30/1423 | . . . . | {the instrument generating sequences of position coordinates corresponding to handwriting (preprocessing or recognising digital ink G06V 30/32)} [2022-01] |
G06V 30/1426 | . . . . | {by sensing position defining codes on a support} [2023-08] |
G06V 30/1429 | . . . | {Identifying or ignoring parts by sensing at different wavelengths} [2023-08] |
G06V 30/1431 | . . . | {Illumination control} [2023-08] |
G06V 30/1434 | . . . | {Special illumination such as grating, reflections or deflections, e.g. for characters with relief} [2023-08] |
G06V 30/1437 | . . . | {Sensor details, e.g. position, configuration or special lenses (G06V 30/1429 takes precedence)} [2023-08] |
G06V 30/144 | . . . | using a slot moved over the image; using discrete sensing elements at predetermined points; using automatic curve following means [2022-01] |
G06V 30/1444 | . . . | {Selective acquisition, locating or processing of specific regions, e.g. highlighted text, fiducial marks or predetermined fields} [2023-08] |
G06V 30/1448 | . . . . | {based on markings or identifiers characterising the document or the area} [2023-08] |
G06V 30/1452 | . . . . | {based on positionally close symbols, e.g. amount sign or URL-specific characters} [2023-08] |
G06V 30/1456 | . . . . | {based on user interactions} [2023-08] |
G06V 30/146 | . . . | Aligning or centring of the image pick-up or image-field [2023-08] |
G06V 30/1463 | . . . . | {Orientation detection or correction, e.g. rotation of multiples of 90 degrees} [2023-08] |
G06V 30/1465 | . . . . | {by locating a pattern (G06V 30/1475 takes precedence; centring within a document with a marking G06V 30/1448)} [2023-08] |
G06V 30/1468 | . . . . . | {Special marks for positioning} [2022-01] |
G06V 30/147 | . . . . | {Determination of region of interest} [2023-08] |
G06V 30/1473 | . . . . | {Recognising objects as potential recognition candidates based on visual cues, e.g. shapes} [2023-08] |
G06V 30/1475 | . . . . | {Inclination or skew detection or correction of characters or of image to be recognised} [2023-08] |
G06V 30/1478 | . . . . . | {of characters or characters lines} [2023-08] |
G06V 30/148 | . . . | Segmentation of character regions [2023-08] |
G06V 30/15 | . . . . | {Cutting or merging image elements, e.g. region growing, watershed or clustering-based techniques} [2023-08] |
G06V 30/153 | . . . . | {using recognition of characters or words} [2022-01] |
G06V 30/155 | . . . . | {Removing patterns interfering with the pattern to be recognised, such as ruled lines or underlines} [2023-08] |
G06V 30/158 | . . . . | {using character size, text spacings or pitch estimation} [2022-01] |
G06V 30/16 | . . | Image preprocessing [2023-08] |
G06V 30/1607 | . . . | {Correcting image deformation, e.g. trapezoidal deformation caused by perspective} [2023-08] |
G06V 30/1613 | . . . | {Interactive preprocessing or shape modelling, e.g. assignment of feature points by a user} [2023-08] |
G06V 30/162 | . . . | Quantising the image signal [2023-08] |
G06V 30/164 | . . . | Noise filtering [2023-08] |
G06V 30/166 | . . . | Normalisation of pattern dimensions [2023-08] |
G06V 30/168 | . . . | Smoothing or thinning of the pattern; Skeletonisation [2023-08] |
G06V 30/18 | . . | Extraction of features or characteristics of the image [2023-08] |
G06V 30/1801 | . . . | {Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes or intersections (extracting features by contour coding G06V 30/182)} [2023-08] |
G06V 30/18019 | . . . . | {by matching or filtering} [2023-08] |
G06V 30/18029 | . . . . . | {filtering with Haar-like subimages, e.g. computation thereof with the integral image technique} [2023-08] |
G06V 30/18038 | . . . . . | {Biologically-inspired filters, e.g. difference of Gaussians [DoG], Gabor filters} [2023-08] |
G06V 30/18048 | . . . . . . | {with interaction between the responses of different filters, e.g. cortical complex cells} [2023-08] |
G06V 30/18057 | . . . . . . . | {Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]} [2023-08] |
G06V 30/18067 | . . . . | {by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation} [2023-08] |
G06V 30/18076 | . . . . | {by analysing connectivity, e.g. edge linking, connected component analysis or slices} [2023-08] |
G06V 30/18086 | . . . | {by performing operations within image blocks or by using histograms} [2023-08] |
G06V 30/18095 | . . . . | {Summing image-intensity values; Projection and histogram analysis} [2023-08] |
G06V 30/18105 | . . . | {related to colour} [2023-08] |
G06V 30/18114 | . . . | {involving specific hyperspectral computations of features} [2023-08] |
G06V 30/18124 | . . . | {related to illumination properties, e.g. according to a reflectance or lighting model} [2023-08] |
G06V 30/18133 | . . . | {regional/local feature not essentially salient, e.g. local binary pattern} [2023-08] |
G06V 30/18143 | . . . | {Extracting features based on salient regional features, e.g. scale invariant feature transform [SIFT] keypoints} [2023-08] |
G06V 30/18152 | . . . . | {Extracting features based on a plurality of salient regional features, e.g. "bag of words"} [2023-08] |
G06V 30/18162 | . . . | {related to a structural representation of the pattern} [2023-08] |
G06V 30/18171 | . . . . | {Syntactic representation, e.g. using a grammatical approach} [2023-08] |
G06V 30/18181 | . . . . | {Graphical representation, e.g. directed attributed graph} [2023-08] |
G06V 30/1819 | . . . | {sparse representations} [2023-08] |
G06V 30/182 | . . . | by coding the contour of the pattern [2023-08] |
G06V 30/1823 | . . . . | {using vector-coding} [2023-08] |
G06V 30/1826 | . . . . | {analysing the spectrum of the contour, e.g. Fourier expansion} [2023-08] |
G06V 30/1829 | . . . . | {using an approximation function} [2023-08] |
G06V 30/1831 | . . . . | {using gradient analysis} [2023-08] |
G06V 30/1834 | . . . . | {using statistical shape modelling, e.g. point distribution model} [2023-08] |
G06V 30/1837 | . . . . | {using wavelet analysis} [2023-08] |
G06V 30/184 | . . . | by analysing segments intersecting the pattern [2023-08] |
G06V 30/186 | . . . | by deriving mathematical or geometrical properties from the whole image [2023-08] |
G06V 30/187 | . . . . | {Frequency domain transformation; Autocorrelation} [2023-08] |
G06V 30/188 | . . . . | {Computation of moments} [2023-08] |
G06V 30/189 | . . . . | {Scale-space domain transformation, e.g. with wavelet analysis} [2023-08] |
G06V 30/19 | . . | Recognition using electronic means [2023-08] |
G06V 30/19007 | . . . | {Matching; Proximity measures} [2023-08] |
G06V 30/19013 | . . . . | {Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching (specially adapted for image segmentation G06T 7/10; specially adapted for the analysis of motion G06T 7/20; specially adapted for image alignment G06T 7/30; specially adapted for the calculation of depth from stereo images G06T 7/50; specially adapted for position determination G06T 7/70)} [2023-08] |
G06V 30/1902 | . . . . . | {Shifting or otherwise transforming the patterns to accommodate for positional errors} [2023-08] |
G06V 30/19027 | . . . . . . | {Matching of contours} [2023-08] |
G06V 30/19033 | . . . . . . . | {by mapping curve parameters onto an accumulator array, e.g. generalised Hough Transform} [2023-08] |
G06V 30/1904 | . . . . . . | {involving a deformation of the sample or reference pattern; Elastic matching} [2023-08] |
G06V 30/19047 | . . . . . . . | {based on a local optimisation criterion, e.g. "snakes", i.e. active contour models of the pattern to be recognised} [2023-08] |
G06V 30/19053 | . . . . . . . | {based on shape statistics, e.g. active shape models of the pattern to be recognised} [2023-08] |
G06V 30/1906 | . . . . . . . . | {based also on statistics of image patches, e.g. active appearance models of the pattern to be recognised} [2023-08] |
G06V 30/19067 | . . . . . . | {Matching configurations of points or features, e.g. constellation matching} [2023-08] |
G06V 30/19073 | . . . . | {Comparing statistics of pixel or of feature values, e.g. histogram matching} [2023-08] |
G06V 30/1908 | . . . . | {Region based matching} [2023-08] |
G06V 30/19087 | . . . . | {based on parametric eigenspace representations, e.g. eigenspace representations using pose or illumination parameters; Shape manifold} [2023-08] |
G06V 30/19093 | . . . . | {Proximity measures, i.e. similarity or distance measures} [2023-08] |
G06V 30/191 | . . . | {Design or setup of recognition systems or techniques; Extraction of features in feature space; Clustering techniques; Blind source separation} [2023-08] |
G06V 30/19107 | . . . . | {Clustering techniques} [2023-08] |
G06V 30/19113 | . . . . | {Selection of pattern recognition techniques, e.g. of classifiers in a multi-classifier system} [2023-08] |
G06V 30/1912 | . . . . | {Selecting the most significant subset of features (G06V 30/19127 takes precedence)} [2023-08] |
G06V 30/19127 | . . . . | {Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods} [2023-08] |
G06V 30/19133 | . . . . | {Interactive pattern learning with a human teacher} [2023-08] |
G06V 30/1914 | . . . . | {Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries, e.g. user dictionaries} [2023-08] |
G06V 30/19147 | . . . . | {Obtaining sets of training patterns; Bootstrap methods, e.g. bagging or boosting} [2023-08] |
G06V 30/19153 | . . . . | {using rules for classification or partitioning the feature space} [2023-08] |
G06V 30/1916 | . . . . | {Validation; Performance evaluation} [2023-08] |
G06V 30/19167 | . . . . | {Active pattern learning} [2023-08] |
G06V 30/19173 | . . . . | {Classification techniques} [2023-08] |
G06V 30/1918 | . . . . | {Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion} [2023-08] |
G06V 30/19187 | . . . . | {Graphical models, e.g. Bayesian networks or Markov models} [2023-08] |
G06V 30/19193 | . . . | {Statistical pre-processing, e.g. techniques for normalisation or restoring missing data} [2023-08] |
G06V 30/192 | . . . | using simultaneous comparisons or correlations of the image signals with a plurality of references [2023-08] |
G06V 30/194 | . . . . | References adjustable by an adaptive method, e.g. learning [2023-08] |
G06V 30/195 | . . . . | {using a resistor matrix} [2023-08] |
G06V 30/196 | . . . | using sequential comparisons of the image signals with a plurality of references [2023-08] |
G06V 30/198 | . . . . | the selection of the next reference depending on the result of the preceding comparison [2022-01] |
G06V 30/1983 | . . . . | {Syntactic or structural pattern recognition, e.g. symbolic string recognition} [2023-08] |
G06V 30/1985 | . . . . . | {Syntactic analysis, e.g. using a grammatical approach (syntactic image representation G06V 30/18171)} [2022-01] |
G06V 30/1988 | . . . . . | {Graph matching (graphical image representation G06V 30/18181)} [2022-01] |
G06V 30/199 | . . | Arrangements for recognition using optical reference masks, e.g. holographic masks [2023-08] |
G06V 30/20 | . . | Combination of acquisition, preprocessing or recognition functions [2023-08] |
G06V 30/22 | . . | characterised by the type of writing [2023-08] |
G06V 30/222 | . . . | of characters separated by spaces [2022-01] |
G06V 30/224 | . . . | of printed characters having additional code marks or containing code marks [2023-08] |
G06V 30/2247 | . . . . | {Characters composed of bars, e.g. CMC-7} [2022-01] |
G06V 30/2253 | . . . . | {Recognition of characters printed with magnetic ink (G06V 30/2247 takes precedence)} [2022-01] |
G06V 30/226 | . . . | of cursive writing [2022-01] |
G06V 30/2264 | . . . . | {using word shape} [2022-01] |
G06V 30/2268 | . . . . | {using stroke segmentation} [2022-01] |
G06V 30/2272 | . . . . . | {with lexical matching} [2022-01] |
G06V 30/2276 | . . . . . | {with probabilistic networks, e.g. hidden Markov models} [2022-01] |
G06V 30/228 | . . . | of three-dimensional handwriting, e.g. writing in the air [2022-01] |
G06V 30/24 | . . | characterised by the processing or recognition method (segmentation of character regions G06V 30/148) [2023-08] |
G06V 30/242 | . . . | Division of the character sequences into groups prior to recognition; Selection of dictionaries [2022-01] |
G06V 30/244 | . . . . | using graphical properties, e.g. alphabet type or font [2022-01] |
G06V 30/2445 | . . . . . | {Alphabet recognition, e.g. Latin, Kanji or Katakana} [2022-01] |
G06V 30/245 | . . . . . | {Font recognition} [2022-01] |
G06V 30/2455 | . . . . . | {Discrimination between machine-print, hand-print and cursive writing} [2022-01] |
G06V 30/246 | . . . . | using linguistic properties, e.g. specific for English or German language [2022-01] |
G06V 30/248 | . . . | {involving plural approaches, e.g. verification by template match; Resolving confusion among similar patterns, e.g. "O" versus "Q" (G06V 30/242 takes precedence)} [2022-01] |
G06V 30/2504 | . . . . | {Coarse or fine approaches, e.g. resolution of ambiguities or multiscale approaches} [2022-01] |
G06V 30/2528 | . . . . | {Combination of methods, e.g. classifiers, working on the same input data} [2022-01] |
G06V 30/2552 | . . . . | {Combination of methods, e.g. classifiers, working on different input data, e.g. sensor fusion} [2022-01] |
G06V 30/26 | . . | Techniques for post-processing, e.g. correcting the recognition result [2023-08] |
G06V 30/262 | . . . | using context analysis, e.g. lexical, syntactic or semantic context [2023-08] |
G06V 30/268 | . . . . | {Lexical context} [2022-01] |
G06V 30/274 | . . . . | {Syntactic or semantic context, e.g. balancing} [2022-01] |
G06V 30/28 | . . | specially adapted to the type of the alphabet, e.g. Latin alphabet [2023-08] |
G06V 30/287 | . . . | {of Kanji, Hiragana or Katakana characters} [2022-01] |
G06V 30/293 | . . . | {of characters other than Kanji, Hiragana or Katakana} [2022-01] |
G06V 30/30 | . . | based on the type of data [2023-08] |
G06V 30/302 | . . . | Images containing characters for discriminating human versus automated computer access [2023-08] |
G06V 30/304 | . . . | Music notations [2022-01] |
G06V 30/32 | . . | Digital ink [2023-08] |
G06V 30/333 | . . . | {Preprocessing; Feature extraction} [2022-01] |
G06V 30/347 | . . . . | {Sampling; Contour coding; Stroke extraction} [2022-01] |
G06V 30/36 | . . . | {Matching; Classification} [2022-01] |
G06V 30/373 | . . . . | {using a special pattern or subpattern alphabet} [2022-01] |
G06V 30/387 | . . . . | {using human interaction, e.g. selection of the best displayed recognition candidate} [2022-01] |
G06V 30/40 | . | Document-oriented image-based pattern recognition [2023-08] |
G06V 30/41 | . . | Analysis of document content (recognition of printed characters based on code marks G06V 30/224) [2023-08] |
G06V 30/412 | . . . | Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables [2022-01] |
G06V 30/413 | . . . | Classification of content, e.g. text, photographs or tables [2022-01] |
G06V 30/414 | . . . | Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text [2022-01] |
G06V 30/416 | . . . | Extracting the logical structure, e.g. chapters, sections or page numbers; Identifying elements of the document, e.g. authors [2022-01] |
G06V 30/418 | . . . | Document matching, e.g. of document images [2022-01] |
G06V 30/42 | . . | based on the type of document [2022-01] |
G06V 30/422 | . . . | Technical drawings; Geographical maps [2022-01] |
G06V 30/424 | . . . | Postal images, e.g. labels or addresses on parcels or postal envelopes [2022-01] |
G06V 30/43 | . . | {Editing text-bitmaps, e.g. alignment, spacing; Semantic analysis of bitmaps of text without OCR} [2022-01] |
G06V 40/00 | Recognition of biometric, human-related or animal-related patterns in image or video data [2023-08] |
G06V 40/10 | . | Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands [2022-01] |
G06V 40/103 | . . | {Static body considered as a whole, e.g. static pedestrian or occupant recognition} [2022-01] |
G06V 40/107 | . . | {Static hand or arm} [2022-01] |
G06V 40/11 | . . . | {Hand-related biometrics; Hand pose recognition} [2022-01] |
G06V 40/113 | . . . | {Recognition of static hand signs} [2022-01] |
G06V 40/117 | . . . | {Biometrics derived from hands} [2022-01] |
G06V 40/12 | . . | Fingerprints or palmprints [2022-01] |
G06V 40/13 | . . . | Sensors therefor [2023-08] |
G06V 40/1306 | . . . . | {non-optical, e.g. ultrasonic or capacitive sensing} [2022-01] |
G06V 40/1312 | . . . . | {direct reading, e.g. contactless acquisition} [2022-01] |
G06V 40/1318 | . . . . | {using electro-optical elements or layers, e.g. electroluminescent sensing} [2022-01] |
G06V 40/1324 | . . . . | {by using geometrical optics, e.g. using prisms (G06V 40/1312 takes precedence)} [2022-01] |
G06V 40/1329 | . . . . | {Protecting the fingerprint sensor against damage caused by the finger} [2022-01] |
G06V 40/1335 | . . . | {Combining adjacent partial images (e.g. slices) to create a composite input or reference pattern; Tracking a sweeping finger movement} [2022-01] |
G06V 40/1341 | . . . | {Sensing with light passing through the finger} [2022-01] |
G06V 40/1347 | . . . | {Preprocessing; Feature extraction} [2022-01] |
G06V 40/1353 | . . . . | {Extracting features related to minutiae or pores} [2022-01] |
G06V 40/1359 | . . . . | {Extracting features related to ridge properties; Determining the fingerprint type, e.g. whorl or loop} [2022-01] |
G06V 40/1365 | . . . | {Matching; Classification} [2022-01] |
G06V 40/1371 | . . . . | {Matching features related to minutiae or pores} [2022-01] |
G06V 40/1376 | . . . . | {Matching features related to ridge properties or fingerprint texture} [2022-01] |
G06V 40/1382 | . . . | {Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger} [2022-01] |
G06V 40/1388 | . . . . | {using image processing} [2022-01] |
G06V 40/1394 | . . . . | {using acquisition arrangements} [2022-01] |
G06V 40/14 | . . | Vascular patterns [2022-01] |
G06V 40/15 | . . | {Biometric patterns based on physiological signals, e.g. heartbeat, blood flow} [2022-01] |
G06V 40/155 | . . | {use of biometric patterns for forensic purposes} [2022-01] |
G06V 40/16 | . . | Human faces, e.g. facial parts, sketches or expressions [2022-01] |
G06V 40/161 | . . . | {Detection; Localisation; Normalisation} [2022-01] |
G06V 40/162 | . . . . | {using pixel segmentation or colour matching} [2022-01] |
G06V 40/164 | . . . . | {using holistic features} [2022-01] |
G06V 40/165 | . . . . | {using facial parts and geometric relationships} [2022-01] |
G06V 40/166 | . . . . | {using acquisition arrangements} [2022-01] |
G06V 40/167 | . . . . | {using comparisons between temporally consecutive images} [2022-01] |
G06V 40/168 | . . . | {Feature extraction; Face representation} [2022-01] |
G06V 40/169 | . . . . | {Holistic features and representations, i.e. based on the facial image taken as a whole} [2022-01] |
G06V 40/171 | . . . . | {Local features and components; Facial parts (eye characteristics G06V 40/18); Occluding parts, e.g. glasses; Geometrical relationships} [2022-01] |
G06V 40/172 | . . . | {Classification, e.g. identification} [2022-01] |
G06V 40/173 | . . . . | {face re-identification, e.g. recognising unknown faces across different face tracks} [2022-01] |
G06V 40/174 | . . . | {Facial expression recognition} [2022-01] |
G06V 40/175 | . . . . | {Static expression} [2022-01] |
G06V 40/176 | . . . . | {Dynamic expression} [2022-01] |
G06V 40/178 | . . . | {estimating age from face image; using age information for improving recognition} [2022-01] |
G06V 40/179 | . . . | {metadata assisted face recognition} [2022-01] |
G06V 40/18 | . . | Eye characteristics, e.g. of the iris [2022-01] |
G06V 40/20 | . | Movements or behaviour, e.g. gesture recognition (recognition of facial expressions G06V 40/16) [2022-01] |
G06V 40/23 | . . | {Recognition of whole body movements, e.g. for sport training} [2022-01] |
G06V 40/25 | . . . | {Recognition of walking or running movements, e.g. gait recognition} [2022-01] |
G06V 40/28 | . . | {Recognition of hand or arm movements, e.g. recognition of deaf sign language (static hand signs G06V 40/113)} [2022-01] |
G06V 40/30 | . | Writer recognition; Reading and verifying signatures [2022-01] |
G06V 40/33 | . . | {based only on signature image, e.g. static signature recognition} [2022-01] |
G06V 40/37 | . . | {based only on signature signals such as velocity or pressure, e.g. dynamic signature recognition} [2022-01] |
G06V 40/376 | . . . | {Acquisition} [2022-01] |
G06V 40/382 | . . . | {Preprocessing; Feature extraction} [2022-01] |
G06V 40/388 | . . . . | {Sampling; Contour coding; Stroke extraction} [2022-01] |
G06V 40/394 | . . . | {Matching; Classification} [2022-01] |
G06V 40/40 | . | Spoof detection, e.g. liveness detection [2022-01] |
G06V 40/45 | . . | {Detection of the body part being alive} [2022-01] |
G06V 40/50 | . | Maintenance of biometric data or enrolment thereof [2022-01] |
G06V 40/53 | . . | {Measures to keep reference information secret, e.g. cancellable biometrics} [2022-01] |
G06V 40/55 | . . | {Performing matching on a personal external card, e.g. to avoid submitting reference information} [2022-01] |
G06V 40/58 | . . | {Solutions for unknown imposter distribution} [2022-01] |
G06V 40/60 | . | Static or dynamic means for assisting the user to position a body part for biometric acquisition [2022-01] |
G06V 40/63 | . . | {by static guides} [2022-01] |
G06V 40/67 | . . | {by interactive indications to the user} [2022-01] |
G06V 40/70 | . | Multimodal biometrics, e.g. combining information from different biometric modalities [2022-01] |
G06V 2201/00 | Indexing scheme relating to image or video recognition or understanding [2022-01] |
G06V 2201/01 | . | Solutions for problems related to non-uniform document background [2022-01] |
G06V 2201/02 | . | Recognising information on displays, dials, clocks [2022-01] |
G06V 2201/03 | . | Recognition of patterns in medical or anatomical images [2022-01] |
G06V 2201/031 | . . | of internal organs [2022-01] |
G06V 2201/032 | . . | of protuberances, polyps nodules, etc. [2022-01] |
G06V 2201/033 | . . | of skeletal patterns [2022-01] |
G06V 2201/034 | . . | of medical instruments [2022-01] |
G06V 2201/04 | . | Recognition of patterns in DNA microarrays [2022-01] |
G06V 2201/05 | . | Recognition of patterns representing particular kinds of hidden objects, e.g. weapons, explosives, drugs [2022-01] |
G06V 2201/06 | . | Recognition of objects for industrial automation [2022-01] |
G06V 2201/07 | . | Target detection [2022-01] |
G06V 2201/08 | . | Detecting or categorising vehicles [2022-01] |
G06V 2201/09 | . | Recognition of logos [2022-01] |
G06V 2201/10 | . | Recognition assisted with metadata [2022-01] |
G06V 2201/11 | . | Technique with transformation invariance effect [2022-01] |
G06V 2201/12 | . | Acquisition of 3D measurements of objects [2022-01] |
G06V 2201/121 | . . | using special illumination [2022-01] |
G06V 2201/122 | . . | Computational image acquisition in electron microscopy [2022-01] |
G06V 2201/13 | . | Type of disclosure document [2022-01] |
G06V 2201/131 | . . | Book [2022-01] |
G06V 2201/132 | . . | Book chapter [2022-01] |
G06V 2201/133 | . . | Survey article [2022-01] |
G06V 2201/134 | . . | Technical report or standard [2022-01] |
G06V 2201/135 | . . | Master, PhD or other thesis [2022-01] |
G06V 2201/136 | . . | Tutorial [2022-01] |