  Skin Segmentation is widely used in biometric applications such as face
detection, face recognition, face tracking, and hand gesture recognition.
However, several challenges such as nonlinear illumination, equipment effects,
personal interferences, ethnicity variations, etc., are involved in detection
process that result in the inefficiency of color based methods. Even though
many ideas have already been proposed, the problem has not been satisfactorily
solved yet. This paper introduces a technique that addresses some limitations
of the previous works. The proposed algorithm consists of three main steps
including initial seed generation of skin map, Otsu segmentation in color
images, and finally a two-stage diffusion. The initial seed of skin pixels is
provided based on the idea of ternary image as there are certain pixels in
images which are associated to human complexion with very high probability. The
Otsu segmentation is performed on several color channels in order to identify
homogeneous regions. The result accompanying with the edge map of the image is
utilized in two consecutive diffusion steps in order to annex initially
unidentified skin pixels to the seed. Both quantitative and qualitative results
demonstrate the effectiveness of the proposed system in compare with the
state-of-the-art works.
