Color-texture image segmentation by combining region and photometric invariant edge information

Authors:
Shengyang Yu;Yan Zhang;Yonggang Wang;Jie Yang
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Department of Computer Science, Nanjing University og Science and Technology, Nanjing, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China
Venue:
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
Year:
2007

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Abstract

An improved approach for JSEG algorithm is proposed for unsupervised color-texture image segmentation. The region and photometric invariant edge information are combined. A novel measure for color-texture homogeneity is defined by weighting the textural homogeneity measure with photometric invariant edge measure. Based on the map whose pixel values are values of the new measure, region growing-merging algorithm used in JSEG is then employed to segment the image. Finally, experiments on a variety of real color images demonstrate performance improvement due to the proposed method.