Creating New Color Space Using Convex Constraint Programming Applied to Skin Color Detection

Abstract

Abstract: Each three-component collection such as {Red, Green, Blue} (RGB), and {Luminance Y,<br><br>Chrominance Cr, Chrominance Cb} (YCbCr) is termed as a color space. Many color spaces are related to each<br><br>other by linear transformations that are captured by 3×3 matrices. Hence a given color, and thereby any color<br><br>image, can be represented in terms of another color space by transforming its 3-d vector representation using the 3<br><br>× 3 matrix. The Main target of this paper is introduce new color transform from viewpoint of convex constraint<br><br>programming. Skin detection is used as benchmark problem for the proposed algorithm. In the New color space,<br><br>the skin and non-skin classes are separated as well. This problem is converted to a convex constraint programming<br><br>which Lagrange multipliers method is used for solving this problem. Founded converting matrix is tested in skin<br><br>detection in simple to complex scene. Obtained results over many databases are compared with existing methods<br><br>which show superiority of the proposed method. Skin and non-skin clusters in the new space color have clustering<br><br>criteria better than RGB and YCbCr color space.