Power line image real-time segmentation method based on self-supervised learning
US12125214B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 20, 2022 |
| Grant date | Oct 22, 2024 |
| Priority date | — |
| Expiry date | Jun 28, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20221
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for segmenting a power line image in real time based on self-supervised learning includes: inputting an input power line sample image and power line sample image mask set for the same batch of images into a region growing algorithm to obtain a single power line sub-image and single power line mask set; randomly extracting at least one single power line image pair for combination, and combining the single power line image pair with a random background picture to generate a power line random background fusion image and power line random background mask set; and carrying out random non-repetitive region growing to obtain image inpainting regions, forming a segmentation mask with the image inpainting regions, obtaining power line segmentation images through an image inpainting algorithm, inputting the power line segmentation images into a power line real-time segmentation network for training, and carrying out predicted segmentation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.