The Study Of Face Recognition And Applications In The Venues Access Control System

Biometric technology has made rapid development in recent decades since the importance of public safety. The biological characteristics are inherent attributes. They have strong self-stability of individual differences, and are automatically the best evidences for authentication. Face Recognition as one of the biometric technologies, is direct, friendly and convenient. It has been widely studied and applied.Since the 1960s Chan & Bledsoe provided using human face for identification, face recognition technology has developed by leaps and bounds, and there have been some typical algorithms and systems. In ideal conditions, these algorithms can make better recognition results, but the actual test results show that, once the conditions change, which are not ideal, its recognition rate will be greatly reduced. The factors which affect the recognition rate are mainly light, expression, age, posture, etc. Therefore, there has a lot of work to do for practical and acceptable public face recognition technology. Based of the existing face recognition technologies, this paper focuses on several key aspects of performance. The main contribution of this paper is summarized as follows:(1) Facial key point location, in particular the exact position of the eyes is the premise of face image cropping and regulation. This paper presents the existing location technologies and points put their shortcomings. Then it presents a joint eyes precise positioning method, and gives the test results and the analysis.(2) Since the illumination has great impact on face recognition, and it usually changes in the low frequency domain, the paper analyses its impaction on image low-frequency coefficients of multi-wavelet decomposition. After that a low-frequency coefficients reconstruction method, which based on the PCA, is proposed. And a full test which based on the classic Eigenface is provided.(3) This paper presents an effectively feature extraction method. It first processes the face image by the LFA (Local Feature Analysis), and gets the LFA feature. After that we decompose the feature by ICA (Individual Component Analysis) method, and use the genetic algorithm (GA) on the decomposed signal for selecting the proposal signal for recognition.(4). In view of the continuous development and updating of face recognition technology, and the new emergence of the large number of new algorithms, we construct a system with the combination of several algorithm blocks as a platform for new algorithm development and simulation.(5). In accordance with the existing face recognition technology and the application in venues access control system, this paper introduce a access control system based on the computer cluster. And according to the requirements of practical application, the system adopts the client\server (C\S) mode. At the same time in order to achieve real-time process rapidly on large database, it introduces a parallel speedup algorithm based on the Intel's MMX\SSE technology. In the last, of this paper, it presents the venues access control system of Good Luck Beijing Sports and the 29th Beijing Olympic Games, and gives the performance of the recognition system.The results of paper not only can be some references in the technical sense of robust face recognition, but also can be a reference for high-speed real-time operating system, a number of algorithms have been successfully applied to the existing our system.