Face Detection Based On The Skin Color And Facial Geometric Features

Human face detection is necessary for face recognition as its first step to locate faces in images. Face detection has been intensively researched and has developed as an independent field.A face detection approach based on the skin color and facial geometric features is presented for its practicability and facility in this paper.We detect skin regions based on color information is researched in the former half of the paper. The first step is preprocessing images, such as filtering the images with low-pass filter, lighting compensation with the different stretching methods in different gray levels. We studied two methods to find face candidates. One is building a Gaussian model of skin-color to segment the skin area, and the other is the method of nonlinear color transformation in YCbCr. The latter method is more effective for varying lighting conditions.Some of segmented regions are faces, some of them are not. We use facial geometric features to decide which ones are real faces. Eye model based on gray-level information and mouth model based on chrominance are constructed respectively, then a triangle model based two eyes and a mouth is employed to verifying each candidate face.The experiment results show that this algorithm is effective to detect faces for color images with clear faces.