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     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.

Collaborators Dr. Guangming Xiong, Beijing Institute of Technology, Beijing, China

Graduate Students:

 Yuchou Chang

Publications:
  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.
(Click image to view paper poster)
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