人臉識別外文文獻

1、Method of Face Recognition Based on Red-BlackWavelet Transform and PCAYuqing Yuqing He, He, Huan Huan He, He, and and Hongying Hongying Yang YangDepartment of Opto-Electronic Engineering,Beijing Institute of Technology,

2、Beijing, P.R. China, 100081 20701170@bit.edu.cnAbstract. Abstract. With the development of the man-machine interface and the recogni-tion technology, face recognition has became one of the most important research aspec

3、ts in the biological features recognition domain. Nowadays, PCA(Principal Components Analysis) has applied in recognition based on many face database and achieved good results. However, PCA has its limitations: th

4、e large volume of computing and the low distinction ability. In view of these limitations, this paper puts forward a face recognition method based on red-black wavelet transform and PCA. The improved histogram equalizat

5、ion is used to realize image pre-processing in order to compensate the illumination. Then, appling the red-black wavelet sub-band which contains the information of the original image to extract the feature and do matchin

6、g. Comparing with the traditional methods, this one has better recognition rate and can reduce the computational complexity.Keywords: Keywords: Red-black wavelet transform, PCA, Face recognition, Improved histogram equa

7、lization.1 Introduction IntroductionBecause the traditional status recognition (ID card, password, etc) has some defects, the recognition technology based on biological features has become the focus of the

8、 re-search. Compared with the other biological features (such as fingerprints, DNA, palm prints, etc) recognition technology, people identify with the people around mostly using the biological characteristics o

9、f human face. Face is the most universal mode in human vision. The visual information reflected by human face in the exchange and contact of people has an important role and significance. Therefore, face recogn

10、ition is the easiest way to be accepted in the identification field and becomes one of most potential iden-tification authentication methods. Face recognition technology has the characteristics of convenient ac

11、cess, rich information. It has wide range of applications such as iden-tification, driver's license and passport check, banking and customs control system, and other fields[1].2.1 2.1 Horizontal Horizontal /V

12、ertical /Vertical Lifting LiftingAs Fig.1 shows, horizontal /vertical lifting is divided into three steps: 1. Decomposition: The original image by horizontal and vertical direction is divided into red and black block i

13、n a cross-block way.2. Prediction: Carry on the prediction using horizontal and the vertical direction four neighborhood's red blocks to obtain a black block predicted value. Then, using the difference of

14、 the black block actual value and the predicted value to substitute the black block actual value. Its result obtains the original image wavelet coefficient. As Fig.1(b) shows:? ? ( , ) ( , ) ( 1, ) ( , 1) ( , 1) ( 1, ) /

15、 4 f i j f i j f i j f i j f i j f i j ? ? ? ? ? ? ? ? ?（1） ( mod 2 mod 2) i j ?3. 3. Revision: Revision:Using the horizontal and vertical direction four neighborhood's black block's wavelet coefficient

16、 to revise the red block actual value to obtain the approximate signal. As Fig.1(c) shows:? ? ( , ) ( , ) ( 1, ) ( , 1) ( , 1) ( 1, ) /8 f i j f i j f i j f i j f i j f i j ? ? ? ? ? ? ? ? ?（2） ( mod 2 mod 2) i

17、j ?In this way, the red block corresponds to the approximating information of the image, and the black block corresponds to the details of the image.2.2 2.2 Diagonal Diagonal Lifting LiftingOn the basis of horizontal /v