FACE RECOGNITION USING TEXTURE AND SHAPE FEATURES

Abstract

newline quotA face recognition system has to associate an identity or name for each face it comes across by matching it to a large database of individuals. Automatic face detection and recognition has been a difficult problem in the field of computer vision for several years. Although humans perform the task in an effortless manner, the underlying computations within the human visual system are of tremendous complexity. Furthermore, the ability to find faces visually in a scene and recognize them is critical for humans in their everyday activities. Consequently, the automation of this task would be useful for many applications including security, surveillance, gaze-based control, affective computing, speech recognition assistance, video compression and animation. newlineDevelopment of automated face recognition system involves addressing challenges such as Facial expression change, Illumination change, Aging, Rotation, Size of the image, Frontal vs. Profile. Overall face recognition mainly consists of three stages. First stage consists of preprocessing of the image. Second consists of describing the face based on the descriptor used or in other words features are extracted from the face based on the descriptors. The third stage consists of obtaining dissimilarity between face images and matching them based on the minimum dissimilarity obtained.quot newline