The Design And Implementation Of Face Recognition System Based On VC + +

Face recognition technology as a kind of extremely has the potential of development in biometric technology, video conference, credit card verification, medical, file management, human-computer interaction, public security system of criminal identification field in a wide range of applications. Due to face recognition has direct, convenient, non-invasive and user friendly, and many other advantages, make it become the current pattern recognition and the field of artificial intelligence a very active research direction. In recent decades, many domestic research of face recognition of scholars have done a lot of research work, and puts forward a lot of practical and efficient face recognition algorithm. The typical face recognition system includes: face image detection, feature extraction, image matching and identification of three parts.This thesis mainly for still images of face recognition is studied, the main involves the following aspects:1.This thesis describes in detail a one-dimensional and two-dimensional Gabor wavelet transform method, and proved by calculation of Gabor filters through the selection of parameters to show facial image. A deep research using 2D Gabor wavelet transform the face of feature extraction method, on feature extraction theory of the traditional Gabor filter based on the face and improvement of the method of feature extraction is proposed based on the face of the valid area Gabor feature extraction algorithm. This method firstly will face image via masks template masking, obtain valid face region within the valid area, in the pixels Gabor feature extraction, outside the territory for effective without any value pixel region, we abandon it, thus greatly reduces the face recognition of time and space complexity. After repeated experiments show that this method can effectively reduce the face feature vector dimension, meanwhile, has Gabor feature extraction algorithm with traditional same robustness.2.This thesis put forward through the analysis, based on the best Gabor characteristics of face recognition method. This method combines the third chapter of face effective mentioned feature extraction algorithm, using regional masks template extraction, eyebrow, nose and eyes lips contains the main face recognition related information, and at the same time selecting Gabor point and sampling, and then under the principal component analysis (PCA) under the method of sampling Gabor characteristics after further dimension reduction, and then using linear differential analysis (LDA) methods are compressed and feature selection.3.This design of face recognition system is based on WindowsXP system in the Visual C++ 6.0 development of lans implementation, and introduces the system detail major parts of the function. Visual C++ 6.0 provide height visualization of application development tools and rich Microsoft Foundation Classes library (MFC library), can make the application development become more simple.