A quick and coarse color image segmentation

In this paper we focus on the problem of image segmentation by color classification. We present a robust agglomerating clustering algorithm based on a cluster validity criteria derived from fuzzy partitions. The result is a simplified segmentation having a small number of large regions. The interest of the proposed method is that it requires a single parameter and that the computational complexity is very low.

[1]  Paul Scheunders,et al.  A genetic c-Means clustering algorithm applied to color image quantization , 1997, Pattern Recognit..

[2]  Thierry Carron,et al.  Symbolic fusion of luminance-hue-chroma features for region segmentation , 1999, Pattern Recognit..

[3]  Noureddine Zahid,et al.  Unsupervised fuzzy clustering , 1999, Pattern Recognit. Lett..

[4]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[5]  Michael A. Arbib,et al.  Color Image Segmentation using Competitive Learning , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Sang Uk Lee,et al.  On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques , 1990, Pattern Recognit..

[7]  Soo-Chang Pei,et al.  Color image segmentation using local histogram and self-organization of Kohonen feature map , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[8]  Nikolaos G. Bourbakis,et al.  A fuzzy region growing approach for segmentation of color images , 1997, Pattern Recognit..

[9]  Jing Li Wang,et al.  Color image segmentation: advances and prospects , 2001, Pattern Recognit..