The Impact of Light Compensation on the Performance of Parametric Skin Detection Model

Skin detection is an essential step for important vision tasks such as the detection, tracking and recognition of face, segmentation of hand for gesture analysis, and person identification. Using skin color as a feature commonly raises problem related to the varying of lighting conditions due to the complex illuminated environment in the real world. Due to this problem, many researchers describe the lighting compensation algorithm as the best solution for such a problem that is indispensable for robust skin-tone color detection. This paper presents a study on the effect of light compensation on a skin color detection model which is based on the 2-dimensional normal distribution of the skin chromatic. A number of images captured in indoor and outdoor environments are used for the experiments to prove the effect of the studied algorithm. The findings show that the lighting compensation technique gives no significant effect on the performance of parametric skin detector model and therefore this problem demands for more research work.