Author : Vinodpuri Rampuri Gosavi and A. K. Deshmane

Face detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. This document demonstrates how a face recognition system can be designed with artificial neural network using Eigen faces. A face authentication system based on principal component analysis and neural networks is proposed to be developed in this paper. The system consists of three stages; preprocessing, principal component analysis, and recognition. In preprocessing stage, normalization illumination, and head orientation were done. Principal component analysis is applied to find the aspects of face which are important for identification. Eigenvectors and eigenfaces are calculated from the initial face image set. New faces are projected onto the space expanded by eigenfaces and represented by weighted sum of the eigenfaces. These weights are used to identify the faces. Neural network is used to create the face database and recognize and authenticate the face by using these weights. In this work, a separate network was built for each person.

Keywords: Face recognition, Face Authentication Principal component analysis (PCA), Artificial Neural network (ANN), Eigenvector, Eigenface.

Article published in International Journal of Current Engineering and Technology, Vol.5, No.1 (Feb-2015)