Global and local binary pattern image crack segmentation method based on robot vision
US11580647B1 · kind B1 · utility
Assignees
Inventors
Key dates
| Filing date | Apr 21, 2022 |
| Grant date | Feb 14, 2023 |
| Priority date | — |
| Expiry date | Apr 21, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30132
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A global and local binary pattern image crack segmentation method based on robot vision comprises the following steps: enhancing a contrast of an acquired original image to obtain an enhanced map; using an improved local binary pattern detection algorithm to process the enhanced map and construct a saliency map; using the enhanced map and the saliency map to segment cracks and obtaining a global and local binary pattern automatic crack segmentation method; and evaluating performance of the obtained global and local binary pattern automatic crack segmentation method. The present application uses logarithmic transformation to enhance the contrast of a crack image, so that information of dark parts of the cracks is richer. Texture features of a rotation invariant local binary pattern are improved. Global information of four directions is integrated, and the law of universal gravitation and gray and roundness features are introduced to correct crack segmentation results, thereby improving segmentation accuracy. Crack regions can be segmented in the background of uneven illumination and complex textures. The method has good robustness and meets requirements of online detection.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.