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

 Abstract-Voiced speech is usually used for speaker recognition. But in text-independent speaker recognition it would be better to use special voiced letters which are appeared in all words. In this paper, we have employed the certain letters for speaker recognition. As we know in Persian language, each consonant letter must be followed by a vowel letter. These are A -I -U -ae-e -ɔ:. Therefore it is enough for text-independent speaker recognition, to find and use these letters. For speaker recognition we employ both vocal source excitation signal and vocal tract system of these letters. Also we use the most prevalent feature parameters for speech/speaker recognition, that is the Mel-frequency cepstral coefficients (MFCC) and for speaker recognition by using vocal source excitation, we have employed Wavelet Octave Coefficients of Residuals (WOCOR). Since these methods are highly sensitive to noise, we use spectral subtraction method to cancel the noise.Index Terms-Source-tract features, Text independent speaker recognition, spectral subtraction, similarity coefficient, Mel-frequency cepstral coefficients.