Adaptive skin color model for hand segmentation

摘要

Hand segmentation is often the first step in applications such as gesture recognition, hand tracking and recognition. We propose a new technique for hand segmentation of color images using adaptive skin color model. Our method captures pixel values of a person's hand and converts them into YCbCr color space. The technique will then map the CbCr color space to CbCr plane to construct a clustered region of skin color for the person. Edge detection is applied to the cluster in order to create an adaptive skin color boundaries for classification. Experimental results demonstrate successful detection over a variety of hand variations in color, position, scale, rotation and pose.