A novel color texture-based segmentation algorithm is proposed. Many powerful color segmentation algorithms such as JSEG (J-SEGmentation) suffer from over segmentation.  An improved JSEG method called improved contrast JSEG (IC-JSEG) is developed to construct the contrast map to obtain the basic contours of the homogeneous regions in the image. A two serial type-based filtering and a noise-protected edge detector are adopted to remove the noise and enhance the edge strength to provide a better contrast map. Based on the combination of improved contrast map and the original J map in JSEG, seed growing-merging method is used to segment the image. Experiments on both natural color-texture images and color medical images show promising results.

Graduate Students:

 Yuchou Chang

1. G.M. Xiong, D.J. Lee, X. Li, J.W. Gong, and H.Y. Chen, “Color Rank and Census Transforms using Perceptual Color Contrast,” IEEE Proceedings of the International Conference on Control, Automation, Robotics and Vision (ICARCV) , p. 1225-1230, Singapore, December 7-10, 2010.
2. G.M. Xiong, D.J. Lee, S.G Fowers, and H.Y. Chen, “Using Perceptual Color Contrast for Color Image Processing,’ Lecture Notes in Computer Science (LNCS), Part III, LNCS 6455, p. 407-416, International Symposium on Visual Computing (ISVC), Las Vegas, NV, U.S.A., November 29-December 1, 2010.

3. Y. Chang, J.K. Archibald, Y. Wang, and D.J. Lee, ?Color-Texture Segmentation of Medical Images Based on Local Contrast Information?, International Journal on Information Technology and Intelligent Computing, vol. 2/4, November 2007.

4. Y. Chang, D.J. Lee, and Y. Wang, ?Color-Texture Segmentation of Medical Images Based on Local Contrast Information?, IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2007), Honolulu, Hawaii, USA, April 1-5, 2007.