Face Recognition Using Snakes Algorithm and Skin Detection Based Face Localization

Skin detection is an important part of face localization since the most exposed part of human skin is the face. This paper proposes a novel algorithm for face localization via skin detection. The algorithm utilizes a kernel iterative procedure to check for the region of interest in an image where it is likely that the face exists. The algorithm utilizes a swarm of particles in a kernel that randomly check the fitness of the corresponding pixel BGR value which is determined from a skin BGR dataset. Consequently, the kernel which has the best fitness value is chosen as the region of the image where it is likely that the face exists. Following this, we employ an active contour model called Snakes algorithm which further converges on our region of interest and finally a contour of the face region is extracted from the original image.