文献类型：期刊文献

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] Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China; [2] State Key Lab. for Novel Software Technology, Nanjing University, Nanjing, 210093, China

年份：2015

卷号：2

起止页码：599

外文期刊名：Proceedings - International Conference on Machine Learning and Cybernetics

收录：EI(收录号：20172403790173)

语种：英文

外文关键词：Color - Color image processing - Image enhancement - Image texture

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. ? 2015 IEEE.