Color Image Porcessing
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.
||Dr. Guangming Xiong, Beijing Institute of
Technology, Beijing, China
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
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.
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.
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.
image to view paper poster)