Research On Single Face Recognition System Based On LDA

With the development of the society, there are increasing demands in effective automatic identity checking. Biometrics is a kind of technology using individual physiological or behavioral characteristics to verify identity. It provides a highly reliable and high stable approach to the identity recognition. Automated face recognition is one of the most concerned branches of biometrics and it is also the one of the most active and challenging tasks for computer vision and pattern recognition at present. Others, they can be used as features for identity check, among all the characteristics of human, the characteristics of face are the most direct means which are friendly and convenient and can easily be accepted by the customers. It is widely applied to public security and security department, such as mug shots retrieval, real-time video surveillance, bank cryptography and so on. Face recognition is an extensive and challenging research problem. Recently, significant progresses have been made in the field of the face recognition technology.It is difficult to implement the face recognition mechanism using computers for several reasons. Human face is a deformable object composing of complex 3D curve surfaces, which is hard to be represented in form of mathematics. And faces of different persons have the similar structure. Furthermore, the face images are greatly dependent on ages and photography conditions. This results that the difference between two face images of two different persons taken under the same photography condition is probably less than that between two images of the same person under different conditions.Therefore, in order to implement a practical face recognition system, the recognition method needs to be independent of the above variations.The thesis collects and studies lots of papers an reports on human face detection and recognition home and abroad of these years. And it puts forward a kind of algorithm for single human face recognition. Experiments prove that the algorithm is reasonable and valuable in theory and practice. The main research work includes:Firstly, in the part of image preprocessing, it uses an advanced algorithm ofintegral projection analysis, and gains good effect.Secondly, in the part of feature extraction, it focuses on PCA and LDA. On the basis of comparison and analysis, it brings forward to associate both in order to increase the recognition ratio. In the part of classification and recognition, it discusses the Nearest Neighbor and K- Nearest Neighbor.Finally, it designs a simple face recognition system to prove the validity, and experiments on the ORL face database. The results show that the algorithm is accessible, and the system is also capable to some extent.