Face Recognition System Using Principle Component Analysis

Abstract

Security and authentication of a person is a crucial part of any industry. There are many techniques used for this purpose. One of them is face recognition. Face recognition is an effective means of authenticating a person. A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. A 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. One of the ways to do this is by comparing selected facial features from the image and a facial database. The advantage of this approach is that, it enables us to detect changes in the face pattern of an individual to an appreciable extent. The recognition system can tolerate local variations in the face expression of an individual. Hence face recognition can be used as a key factor in crime detection mainly to identify criminals. There are several approaches to face recognition of which Principal Component Analysis (PCA) have been incorporated in our project. The system consists of a database of a set of facial patterns for each individual. The characteristic features called ‘eigenfaces’ are extracted from the stored images using which the system is trained for subsequent recognition of new images. Divyan Rawal Kaushlendra Kumar Pandey Shiva Aggarwal Project Supervisor