The Research Of Human Face Recognition Algorithm Based On PCA

Face recognition is a kind of technology which can complete recognizing face by processing and analyzing the face image in the computer and extracting the representation of face image from the processed image. Face Recognition System(FRS) is comprised of three parts: Preprocessing, Feature extraction and the most important technology is feature extraction. At present, there are many technologies of face recognition and each of them has its characteristic o In this article, the popular face recognition technologies are introduced and the method called Principle Component Analysis (PCA) which uses the eigen-face to classify the face images is discussed in details。The main research work of this article is as follows:(1)The face recognition research background, research content, probably introduced the face recognition system, at the same time, the image of some of the major methods for approximate summary.(2) The principal component analysis algorithm and block algorithm. Principal component analysis algorithm is the most effective and the most representative identification method, but the traditional PCA method to extract the image characteristics, the change of the external environment influence is relatively large. For such reasons, we introduce a sub division method, namely PCA block. The method is that:in image feature extraction, first the image is divided, and then the sub image using PCA method to extract the feature vector. This paper presents an improved PCA block of the new algorithm, breaking the traditional block PCA method in seeking scatter matrix when no image pairs are considered the difference(3) The research of the two-dimensional PCA algorithm and block PCA algorithm. PCA method using feature extraction, it is the first step to the image data is transformed into a one-dimensional vector, it is a direct impact:images of the vector dimension too much. Because of this situation, this article will PCA method is extended to two dimensional PCA, will PCA block to block two dimensional PCA. Due to the two-dimensional PCA method directly uses the image matrix scatter matrix, the scatter matrix dimension is much lower than the PCA method to obtain the covariance matrix.(4) The traditional2DPCA on the image data without distinction, this paper presents wavelet transform under the2DPCA algorithm. This algorithm not only saved the time of recognition,but also improved the face recognition rate, and the experiment proves its effectiveness.