Abstract—one of the best way to clustering in color images is to transform R, G, B color space into the target color space by linear transformations that are captured by 3×3 matrices. The Main target of this paper is introducing new color transform from viewpoint of convex constraint programming. Lip detection is used as benchmark problem for the proposed algorithm. In the New color space, the Lip and non-Lip classes are separated as well. This problem is converted to a convex constraint programming which Genetic Algorithm is used for solving this problem. Founded converting matrix is tested in Lip detection in simple to complex scene. Obtained results over many databases are compared with existing methods which show superiority of the proposed method.

Index Terms—Genetic Algorithm, Color space, convex constraint programming, Lip detection, clustering criteria.

Cite: Seyyed Meysam Hosseini, Hasan Farsi, and Hadi Sadoghi Yazdi, "Best Clustering Around the Color Images," International Journal of Computer and Electrical Engineering vol. 1, no. 1, pp. 20-24, 2009.