Real-Time Face Recognition Using Adaptive Skin-Color Model

In a real-time face recognition system, complex background that occurs in an image or video can degrade the accuracy of both face detection and recognition due to the uncontrolled environment. However, few studies have been proposed to address this issue. In this paper, we propose an adaptive skin color model to make the system more reliable. First, real face region is elected among face-like regions with skin color detection. Then, additional objects (i.e., background, hair and clothes) are omitted in face image by using a 2-D skin color model. It is shown that the speed of the algorithm proposed is almost the same as classical ones, while the recognition rate improves about 10% in crowd or blurry background.