Practical Face Image Verification System Design

Face recognition and verification is an important field in image processing and pattern recognition research. It is valuable on the identity verification aspect.This paper divides the system into four parts via the detailed analysis of face verification systems, which are face detection, face image alignment, feature extraction, classification. Through the research in graduate study and the collaboration with others, the traditional face detection algorithm is analyzed and the Adaboost based algorithm is applied to detect the face images in the video; in the face image alignment model, the face image is aligned based on the eye position, and aiming at the advantages and disadvantages the Multi-band Gabor filtering fusion is presented for localizing eyes and aligning the face images; then a set of 40 Gabor filters is applied to extract the Gabor feature of the aligned face images; lastly the R-LDA is applied as the classifier to solve the small sample size problem in the Fisher criterion and finish the verification task. At last, a prototype of face verification system is finished. This system can automatically detect the face images, and align them based on the eyes'position, and verify the people based on the Gabor feature extracted from the aligned face images.Through the experiments, it is proved that the algorithms presented and applied in this paper are robust, and has obvious advantages compared with the traditional algorithms. And the software based on those algorithm can complete the automatic face detection and verification task.