Research On Human Face Detection And Recognition

Face recognition technology (FRT) is one of the most active research topics in areas of image processing, pattern recognition and artificial intelligence recent years. It includes two parts: face detection and face recognition. This dissertation focuses on research of frontal face detection and recognition of color, monochrome and sketch images. Furthermore, the author also establishes a face recognition simulation system.In order to detect frontal face, a method which combined skin color detection and validated spatial facial features scope is presented. The distribution and characteristic of skin color is firstly studied in color space to establish effective skin color model and to use it in image segmentation. Then, some unseemliness regions in segmentation are eliminated according to moment features. At last, we locate the facial features based on the acquired skin color, and to validate whether this face region contains face or not according to the relative location among features. The experiment results show that this method decrease false detection rates enormously.A new algorithm for face recognition based on wavelet transform and hidden Markov model (HMM) is proposed. The original image is decomposed into low frequency and high frequency sub-band images by applying three-level wavelet transformation. As a result, three groups of wavelet features which correspond to low frequency, horizontal details and vertical details are obtained. Kernel principal component analysis (KPCA) is then performed on each group in frequency. These three groups after KPCA are combined together by using a feature fusion method, and served as observation vectors of HMM. A set of images representing different instances of the same person are used to train each HMM. Then the optimal model parameters are used in face recognition. Furthermore, the author also works on face sketch recognition. The author presents a novel sketch-to-photo transformation method in order to transform sketch recognition to face photo recognition for face sketch recognition more easily.At last, a face recognition simulation system is established. The experiment results show that it is not only suitable to multi-expression recognition but also robust to different types of images.