Abstract
In this paper, we employed a new approach to detect human faces in color images. A binary skin color map is firstly obtained by applying the skin/non-skin classification algorithm, and then the integral image representation is used to preprocess the skin and intensity map. Thereafter, the refined skin areas are selected from input image for further detection. In the next processing, an intensity distribution model, which can be calculated on integer image very quickly, is used to decide whether the selected skin area contains a face candidate or not. In the possible face areas a new approach is designed to locate eyes accurately. Based on the positions of eyes, the other facial features are located and then the geometrical information of all facial features is used to further verify human face. Experiment results show the proposed method can successfully detect the frontal human faces with a wide range of variations in color, lighting, scale and expression from color image with complex backgrounds.