An Efficient Face Recognition Technique Using PCA and Artificial Neural Network
Ganesan Karthik, Sateesh Kumar · 2014
Face recognition is one of the biometric tool for authentication and verification. It is having both research and practical relevance. . Face recognition, it not only makes hackers virtually impossible to steal one's password, but also increases the userfriendliness in human-computer interaction. Facial recognition technology (FRT) has emerged as an attractive solution to address many contemporary needs for identification and the verification of identity claims. A facial recognition based verification system can further be deemed a computer application for automatically identifying or verifying a person in a digital image.The two common approaches employed for face recognition are analytic (local features based) and holistic (global features based) approaches with acceptable success rates. In this paper, we present a hybrid features based face recognition technique using principal component analysis technique.Principal component analysisis used to compute global feature while the local feature are computed configuring the central moment and Eigen vectors and the standard deviation of the nose,mouth and eyes segments of the human face as the decision support entities of Artificial neural network.