Skin color detection using artificial immune networks

Skin detection is the key technology in various image processing applications such as face detection. The aim of skin detection is to determine if a color pixel is a skin or non-skin color. Skin color is often considered to be a useful and discriminating image feature for facial area since it provides computationally effective yet, robust to variation in scale, orientation and partial occlusion. Nevertheless, skin detection is also an extremely challenging task since the skin color is sensitive to various factors such as illumination, ethnicity, individual characteristics and subject appearances. In this paper, an artificial immune network based skin detection scheme in several skin color spaces is proposed. Particle swarm optimization is employed to train/optimize skin/non-skin immune network classifiers. The performance of the method was evaluated employing images derived from the Internet.