Study On Some Algorithms In Face Recognition

Human face recognition is an important subject in the area of pattern recognition, which has a wide range of potential applications.This paper researched facial feature location and principal component analysis in face recognition, and then realized static facial image recognition. The works of this paper are listed as follows:(1) Based on the history and content of face recognition, summarized the application and development of face recognition. Introduced main face databases and the database used in this paper.(2) Researched and realized Active Shape Model and Active Appearance Model.(3) Put forward an improved facial feature location algorithm based on ASM and AAM. The algorithm combines the advantages of ASM and AAM. The algorithm improved the locating accuracy.(4) Researched principal component analysis in face recognition, and then proposed an improved PCA method combined with edges. The algorithm improved the face recognition rate.(5) Realized a static facial image recognition system based on improved PCA method. Achieved an improved principal component analysis and a database management system in real-time face recognition system.The initiative works of this paper is:(1) Researched ASM and AAM, and then proposed an improved facial feature focation algorithm based on ASM and AAM. The algorithm combines the local ASM model, AAM texture constraints and the process of parameter optimization based on linear regression. The experimental result indicates that, the improved algorithm has a bigger enhancement in the accuracy and robustness.(2) Improved PCA method. Proposed a new PCA method combined with edges. The method distinguished between different facial features. And boundary information was integrated into PCA. The experimental results show that the recognition rate is superior to traditional PCA.