EE 368 Project: Face Detection in Color Images

We present in this report an approach to automatic detection of human faces in color images. The proposed approach consists of three parts: a human skin segmentation to identify probable regions corresponding to human faces; adaptive shape analysis to separate isolated human faces from initial segmentation results; and a view-based face detection to further identify the location of each human face. The human skin segmentation employs a model-based approach to represent and differentiate the background colors and skin colors. To further refine the initial segmentation results, the adaptive shape analysis uses a series of morphological operations based on the prior shape knowledge of upright human faces. The view-based face detection is constructed based on principal component analysis and neural network classification. Our face detector has been applied to several test images, and satisfactory results have been obtained. Index Terms – Human skin segmentation, Gaussian mixture model, Adaptive shape analysis, Principal component analysis, and Neural network.