A Novel Color Space Creating Method Applied to Skin Color Detection

Abstract

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.

Prediction of Total Soluble Solids and pH of Strawberry Fruits Using RGB, HSV and HSL Colour Spaces and Machine Learning Models

“…According to the findings of the sensitivity analysis, it can be concluded that the S and H were the most and least influential factors, corresponding to predict TSS and pH for both models. Some published articles also reported similar results on the importance of colour channels in object detection [ 89 , 90 ].…”