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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 G06V10/56)

Introduced: January 2022

Title

Titles differ between systems:

IPC: Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features

CPC: 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 G06V10/56)

Full Title

Full titles differ between systems:

IPC:

Arrangements for image or video recognition or understanding > Extraction of image or video features > Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features

CPC:

Arrangements for image or video recognition or understanding (character recognition in images or video G06V30/10) > Extraction of image or video features > 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 G06V10/56)

Additional Content IPC

Glossary

BOF bag of features, see BOW BOVF bag of visual features, see BOVF BOVW bag of visual words, see BOW BOW bag of words, a model originally developed for natural language processing; when applied to images, it represents an image by a histogram of visual words, each visual word representing a specific part of the feature space. MSER maximally stable extremal regions, a technique used for blob detection RANSAC random sample consensus, a popular regression algorithm SIFT scale-invariant feature transform superpixels superpixel sets of pixels obtained by partitioning a digital image for saliency assessment SURF speeded up robust features

Limiting references

Colour feature extraction

Of 4 combined children, 0 exist in both systems.

4 codes are CPC-only extensions.

Child Classifications

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Top Applicants

Top Applicants (IPC)

Class G06,2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 66,669
  2. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,313
  3. MICROSOFT TECHNOLOGY LICENSING US 41,918
  4. GOOGLE US 32,969
  5. SGCC(STATE GRID CORPORATION OF CHINA) 30,822
  6. INTEL CORPORATION US 30,010
  7. TENCENT TECHNOLOGY (SHENZHEN) COMPANY 28,235
  8. HUAWEI TECHNOLOGIES COMPANY CN 26,079
  9. APPLE US 21,891
  10. HUAWEI TECHNOLOGIES COMPANY 20,505

Top Applicants (CPC)

Class G06,2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 76,952
  2. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,841
  3. MICROSOFT TECHNOLOGY LICENSING US 44,778
  4. GOOGLE US 35,735
  5. INTEL CORPORATION US 32,087
  6. HUAWEI TECHNOLOGIES COMPANY CN 30,572
  7. TENCENT TECHNOLOGY (SHENZHEN) COMPANY 25,023
  8. APPLE US 23,482
  9. SGCC(STATE GRID CORPORATION OF CHINA) 22,548
  10. HUAWEI TECHNOLOGIES COMPANY 20,917