Study On Key Issues Of Gate-Entry Control System Based On Face Recognition For Large-Scale Users

Automatic face recognition is a typical pattern analysis, understanding and classification problem, and is closely related to pattern recognition, image processing, computer vision, intelligent human-computer interaction, cognitive psychology etc. It is believed that face recognition has a great deal of potential application in public security, information security and other fields.In this thesis, the core techniques and key issues are studied, aiming at developing a robust and practical gate-entry control system based on face recognition for large-scale users. The main content and innovations of the thesis involve:1. The multi-classifier cascade face detection method and continuous adaptive MeanShift face tracking technique are studied to attain real-time face detection in the system. A support vector machine and Hough transform based eye localization method is proposed for face image's normalization. Compare to existing eye localization methods, there is no need to set parameters and build templates in the proposed method and the localization is simple and easy to implement. At the same time, it is of definite robustness to face rotation in image plane,scale and facial expression variation. In terms of localization results, the localization velocity of the proposed method is faster and the localization accuracy is higher;2. In order to solve recognition rate reduction resulting from illumination,pose etc moderate variations to some extent, the Kernel Direct Discriminant Analysis method is studied and a corrected model and a fractional power polynomial kernel function are first employed in the method. Through experiments on face databases with multi-poses and multi-illumination conditions, the results indicate that in contrast to other methods based on Kernel, the method is of higher recognition rate and more robustness to the above variations. When corrected model and fractional power polynomial kernel function are applied, its robustness is improved further;3. Hybrid Genetic Algorithms based method which introduces Simulated Annealing concept into traditional Genetic Algorithms is studied to reduce the dimension of local facial features extracted by Gabor transformation. It not only effectively solves the"premature"and optimization stagnancy problems existing in traditional Genetic Algorithms, its stability and optimization performance is also...