文献类型：会议论文

英文题名：IMAGE SEGMENTATION WITH TEXTURE CLUSTERING BASED JSEG

作者：Zhang, Jing[1,2];Gao, Yong-Wei[1];Feng, Sheng-Wei[1];Chen, Zhi-Hua[1];Yuan, Yu-Bo[1]

机构：[1]E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China;[2]Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210093, Jiangsu, Peoples R China

会议论文集：International Conference on Machine Learning and Cybernetics (ICMLC)

会议日期：JUL 12-15, 2015

会议地点：Guangzhou, PEOPLES R CHINA

语种：英文

外文关键词：Image segmentation; JSEG; Color information; Texture structure

摘要：Image segmentation is one of the most crucial techniques in computer vision. In this paper, we propose an improved approach for color image segmentation, Texture clustering based JSEG (T-JSEG). The T-JSEG combines the texture information with the classical JSEG algorithm. We use the Gabor feature clustering to produce texture map and combine it with color map to achieve a new map for J value computing. The color image segmentation result is improved by adding the texture information to the JSEG. Experiments on natural color images of Berkeley Segmentation Database verify that our method is very effective on color image segmentation and more accurate boundaries of regions are found in comparison with the classical JSEG algorithm.