Research On Face Recognition And Its Application

Face recognition is a complex and difficult problem which is important for surveillance and security, telecommunication, digital libraries, video meeting, and human-computer intelligent interaction. Despite the fact that human faces are essentially similar, we are very skilled at recognizing the identities of people from their faces. We can perform this task very easily and it is a basic and important social act although we are still puzzled with the psychological and physiological nature of the process.The main contributions of this work are listed as follows:1) Based on algebraic features of the images,this paper first introduced the PCA-Based face recognition algorithm. Some research has done on the selection of the eigenvector which used to create the eigen-space,the distance measure methods and the selection of the training set.2) This paper introduced theory of LDA algorithm and its application to face recognition and acquired a great many experiments.3) Face feature extraction algorithm based on Gabor transform is introduced. Compared with Fourier transform,Gabor transform is proved to be better in face feature extraction. And then,A fast algorithm of Gabor Transform is introduced.4) A face recognition algorithm base on Gabor wavelet transform is studied The algorithm studied in this paper consists of three steps:Gabor wavelet is first applied to face images, and then reduce the dimensionality of Gabor eigenvector via PCA. at last, we use LDA to obtain the best projection direction for classification purposes. The improved performance of this new algorithm over pure PCA algorithm is demonstrated by our experiments.