Human Facial Image Recognition Algorithm Based on Singular Value Features and Statistical Model

Human facial image recognition is a frontier topic of pattern recognition.The state of the art in this research field still lies in low level up till now. In respect of facial image feature extraction,most researchers have adopted 1-D and 2-D geometric features of facial image for image recognition.However,the effectiveness of these features to recognition is open to question.We proved that Singular Value feature vector has some im portant properties of algebraic and geometric invariance and insensitiveness to noise Therefore,we use SV features to recognize human face by a normal pattern Bayes classifier based on Sammon’s optimal discriminant plane in our experiment,the statistical recognition model.which is constructed by using 9 photos,can recognize these photos.It is interesting to note that our model can recognize photos of one person taken in different period