Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection

This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and nonskin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11], [12]. key words: face detection, normalized RGB, chromaticity diagram, histogram thresholding, coarse skin region, fine skin region