Unsupervised Color-texture Image Segmentation

• Published in: Shanghai jiao tong da xue xue bao Vol. 13; no. 1; pp. 71 - 75
• Main Author: 郁生阳 张艳 王永刚 杨杰
• Format: Journal Article
• Language: English
• Published: Heidelberg Shanghai Jiaotong University Press 01.02.2008; Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China%Department of Computer Science, Nanjing University of Science and Technology, Nanjing 210094, China
• Subjects: Architecture; Computer Science; Electrical Engineering; Engineering; Life Sciences; Materials Science; 信号识别; 图象处理; 计算机技术; 识别模式; photometric color invariance; color-texture segmentation; TP 391; edge detection; value segmentation (JSEG); region growing; J value segmentation (JSEG)
• ISSN: 1007-1172; 1995-8188
• DOI: 10.1007/s12204-008-0071-2

The measure J in J value segmentation （JSEG） fails to represent the discontinuity of color, which degrades the robustness and discrimination of JSEG. An improved approach for JSEG algorithm was proposed for unsupervised color-texture image segmentation. The texture and photometric invariant edge information were combined, which results in a discriminative measure for color-texture homogeneity. Based on the image whose pixel values are values of the new measure, region growing-merging algorithm used in JSEG was then employed to segment the image. Finally, experiments on a variety of real color images demonstrate performance improvement due to the proposed method.