Face Recognition Based On Visual Feature Extraction And Kernel Discriminant Analysis

Face recognition has a variety of potential applications in public security, surveillance, law enforcement, commerce, identity authentication, human-computer interfaces and e-services. During the past years, face recognition has received significant attention as a booming technology. In field settings, face images are subject to a wide range of variations. These include pose or view angle, illumination, occlusion, facial expression, time delay between image acquisition, and individual differences. The scalability of face recognition systems to such factors is not well understood. Face recognition in a perception system from human beings seems instinctive, but it is really a tough and complex task for a machine-based system. Recent face recognition surveys reveal that lighting changes, indoor-outdoor changes, pose variations and elapsed time databases are the critical parameters that greatly influence the performance of a face recognition system. But the effect from those parameters is significantly database dependent. Also, face recognition technology is related to the knowledge of image processing, pattern recognition, psychophysics and neuroscience. The human face is conformable in structure, and is elastic and deformable locally. The study of face recognition will improve the target recognition of the same kind.A general statement of the problem of machine recognition of faces can be formulated as follows: given still or video images of a scene, identify or verify one or more persons in the scene using a stored database of faces. The aim of this study is to...