Abstract: This paper proposed a method for skin segmentation based on the similarity of skin??tone given by strengthened classifier which constructed via Real AdaBoost algorithm and dynamic on the clustering property of skin??tone distribution in YCrCb chrominance space, a set of weak classifiers in Look??Up??Table (LUT) type using circle??like features was trained via Real AdaBoost to form a strengthened classifier. Firstly, gray scale images indicated the skin??tone similarity of the pixels was created by processing the images with the strengthened classifier. Then skin segmentation was implemented according to the dynamic threshold selected through Da??Jing method. The experimental results show that the strengthened classifier has an outstanding ability for describing the distribution of skin??tone color in the YCrCb space. The method is robust, and efficient.
??Key words: skin segmentation; Real AdaBoost algorithm; Look??Up??Table (LUT) type; circle??like weak classifier; YCrCb chrominance space; skin??tone color distribution
