Skin Detection and Segmentation of Human Face in Color Images

Abstract

This paper presents the procedures of face segmentation in the color image based on skin detection through the establishment of skin model and the segmentation of skin region. Firstly, in order to reduce the effect of factors on the segmentation of face region, a method for compensating the color of input images is used to alleviate the interferences from bad illuminating conditions. Secondly, Gaussian model about skin information is established which can be used to detect skin pixels in color images and transform color images to gray-scale images. Thirdly, a new algorithm of Otsu is used to find out the skin regions in binary images. Finally, mathematical morphology operator and prior knowledge are used to find out the face regions and discard regions that are similar to the skin in color. This method can deal with various sizes of faces, different illumination conditions, diverse poses and changeable expressions. In particular, the scheme significantly increases the execution speed of the face segmentation algorithm in the case of complex backgrounds. The experiments show that this method reduces the computation of the procedure, and at the same time improves the detection speed and efficiency.