The Analysis, Improvement And Implementation Of Face Recognition Based On Statistical Feature

Comparing with other technologies of biometric recognition, the technology of face recognition has so many advantages such as non-intrusive, easy-collection and high-accuraccy that it is popular and has become a hot researched field in biometric recognition. Face recognition methods can be divided into two classes generally, based on geometry feature and based on statistical feature.Statistical feature is our main research job. Many kinds of methods based on it, such as methods based on principle component analysis, based on linear discriminant analysis and based on sigular value decomponent, are researched systemically, and compared by recognition rates. On the one hand, some disadvandages of these methods are found out and new methods are advanced to improve the accuraccy. On the other hand, the principle of these new methods are explained in detail and compared with their old methods by mass experimental datas, which indicate the advantages of these new methods. Finally, all the arithmetic is realized with c/c++ language attached friendly interface to make manipulation easy.