The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jun. 15, 2021
Filed:
Oct. 30, 2020
China Institute of Water Resources and Hydropower Research, Beijing, CN;
Wenlong Song, Beijing, CN;
Rui Tang, Beijing, CN;
Juan Lv, Beijing, CN;
Jingxuan Lu, Beijing, CN;
Kun Yang, Beijing, CN;
Zhicheng Su, Beijing, CN;
Yuanyuan Duan, Beijing, CN;
Xuejun Zhang, Beijing, CN;
Lihua Zhao, Beijing, CN;
Yizhu Lu, Beijing, CN;
Hongjie Liu, Beijing, CN;
Abstract
A Region Merging image segmentation algorithm based on boundary extraction is disclosed, comprising the steps of calculating a gradient image, extracting a boundary and carrying out initial segmentation and Region Merging, wherein each pixel is regarded as one region when initial segmentation is not conducted. In the Region Merging process, the portion of the common boundary of two adjacent regions that lies on the boundary image is taken as the merging cost, the regions are merged according to the ascending order of the mean gradient value inside the region, and a texture difference evaluation mechanism is introduced to reduce the wrong segmentation. The algorithm solves the problems of the other current segmentation algorithms, such as over-segmentation, easy to be influenced by noise and illumination, large in computation and memory consumption, in need of a large number of samples being marked manually and the like. Besides, all regions or all categories achieve the best segmentation result on one final segmentation result. These advantageous features can reduce the computational resource consumption of subsequent tasks and improve their results.