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  • G06V10/00
    		•  Arrangements for image or video recognition or understanding (character recognition in images or video G06V 30/10) [2022.01] HB CC 5L096
  • G06V10/10
    		•  .Image acquisition (document image scanning and transmission H04N 1/00; control of digital cameras H04N 5/232) [2022.01] HB CC 5L096
  • G06V10/12
    		•  ..Details of acquisition arrangements; Constructional details thereof [2022.01] HB CC 5L096
  • G06V10/14
    		•  ...Optical characteristics of the device performing the acquisition or on the illumination arrangements [2022.01] HB CC 5L096
  • G06V10/141
    		•  ....Control of illumination [2022.01] HB CC 5L096
  • G06V10/143
    		•  ....Sensing or illuminating at different wavelengths [2022.01] HB CC 5L096
  • G06V10/145
    		•  ....Illumination specially adapted for pattern recognition, e.g. using gratings [2022.01] HB CC 5L096
  • G06V10/147
    		•  ....Details of sensors, e.g. sensor lenses(fingerprint or palmprint sensors G06V 40/13; vascular sensors G06V 40/145;eye sensors G06V 40/19) [2022.01] HB CC 5L096
  • G06V10/20
    		•  .Image preprocessing [2022.01] HB CC 5L096
  • G06V10/22
    		•  ..by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition [2022.01] HB CC 5L096
  • G06V10/24
    		•  ..Aligning, centring, orientation detection or correction of the image [2022.01] HB CC 5L096
  • G06V10/25
    		•  ..Determination of region of interest [ROI] or a volume of interest [VOI] [2022.01] HB CC 5L096
  • G06V10/26
    		•  ..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 [2022.01] HB CC 5L096
  • G06V10/28
    		•  ..Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns [2022.01] HB CC 5L096
  • G06V10/30
    		•  ..Noise filtering [2022.01] HB CC 5L096
  • G06V10/32
    		•  ..Normalisation of the pattern dimensions [2022.01] HB CC 5L096
  • G06V10/34
    		•  ..Smoothing or thinning of the pattern;Morphological operations;Skeletonisation [2022.01] HB CC 5L096
  • G06V10/36
    		•  ..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 [2022.01] HB CC 5L096
  • G06V10/40
    		•  .Extraction of image or video features [2022.01] HB CC 5L096
  • G06V10/42
    		•  ..Global feature extraction by analysis of the whole pattern, e.g. using frequency domaint ransformations or autocorrelation [2022.01] HB CC 5L096
  • G06V10/422
    		•  ...for representing the structure of the pattern or shape of an object therefor [2022.01] HB CC 5L096
  • G06V10/424
    		•  ....Syntactic representation, e.g. by using alphabets or grammars [2022.01] HB CC 5L096
  • G06V10/426
    		•  ....Graphical representations [2022.01] HB CC 5L096
  • G06V10/44
    		•  ..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 [2022.01] HB CC 5L096
  • G06V10/46
    		•  ..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) [2022.01] HB CC 5L096
  • G06V10/48
    		•  ..by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation [2022.01] HB CC 5L096
  • G06V10/50
    		•  ..by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis [2022.01] HB CC 5L096
  • G06V10/52
    		•  ..Scale-space analysis, e.g. wavelet analysis (multiscale boundary representations G06V 10/42) [2022.01] HB CC 5L096
  • G06V10/54
    		•  ..relating to texture [2022.01] HB CC 5L096
  • G06V10/56
    		•  ..relating to colour [2022.01] HB CC 5L096
  • G06V10/58
    		•  ..relating to hyperspectral data [2022.01] HB CC 5L096
  • G06V10/60
    		•  ..relating to illumination properties, e.g. using a reflectance or lighting model [2022.01] HB CC 5L096
  • G06V10/62
    		•  ..relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking [2022.01] HB CC 5L096
  • G06V10/70
    		•  .using pattern recognition or machine learning(optical pattern recognition or electronic computations therefor G06V 10/88) [2022.01] HB CC 5L096
  • G06V10/72
    		•  ..Data preparation, e.g. statistical preprocessing of image or video features [2022.01] HB CC 5L096
  • G06V10/74
    		•  ..Image or video pattern matching; Proximity measures in feature spaces [2022.01] HB CC 5L096
  • G06V10/75
    		•  ...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 [2022.01] HB CC 5L096
  • G06V10/762
    		•  ..using clustering, e.g. of similar faces in social networks [2022.01] HB CC 5L096
  • G06V10/764
    		•  ..using classification, e.g. of video objects [2022.01] HB CC 5L096
  • G06V10/766
    		•  ..using regression, e.g. by projecting features on hyperplanes [2022.01] HB CC 5L096
  • G06V10/77
    		•  ..Processing image or video features in feature spaces; using data integration or data reduction,e.g. principal component analysis [PCA] or independent component analysis [ICA] or selforganising maps [SOM]; Blind source separation [2022.01] HB CC 5L096
  • G06V10/771
    		•  ...Feature selection, e.g. selecting representative features from a multi-dimensional feature space [2022.01] HB CC 5L096
  • G06V10/772
    		•  ...Determining representative reference patterns,e.g. averaging or distorting patterns;Generating dictionaries [2022.01] HB CC 5L096
  • G06V10/774
    		•  ...Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting [2022.01] HB CC 5L096
  • G06V10/776
    		•  ...Validation; Performance evaluation [2022.01] HB CC 5L096
  • G06V10/778
    		•  ...Active pattern-learning, e.g. online learning of image or video features [2022.01] HB CC 5L096
  • G06V10/80
    		•  ...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) [2022.01] HB CC 5L096
  • G06V10/82
    		•  ..using neural networks [2022.01] HB CC 5L096
  • G06V10/84
    		•  ..using probabilistic graphical models from image or video features, e.g. Markov models or Bayesian networks [2022.01] HB CC 5L096
  • G06V10/86
    		•  ..using syntactic or structural representations of the image or video pattern, e.g. symbolic string recognition; using graph matching [2022.01] HB CC 5L096
  • G06V10/88
    		•  .Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters [2022.01] HB CC 5L096
  • G06V10/94
    		•  .Hardware or software architectures specially adapted for image or video understanding [2022.01] HB CC 5L096
  • G06V10/96
    		•  .Management of image or video recognition tasks [2022.01] HB CC 5L096
  • G06V10/98
    		•  .Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns [2022.01] HB CC 5L096
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