Face Recognition using Eigenfaces and Neural Networks
Abstract
In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an unknown face by using the backpropagation neural network that utilized euclidean distance for classification and recognition. The ORL database for this investigation consists of 40 people with various 400 face images had been used for the learning. The eigenfaces including implemented Jacobi’s method for eigenvalues and eigenvectors has been performed. The classification and recognition using backpropagation neural network showed impressive positive result to classify face images.
DOI: https://doi.org/10.3844/ajassp.2006.1872.1875
Copyright: © 2006 Mohamed Rizon, Muhammad Firdaus Hashim, Puteh Saad, Sazali Yaacob, Abdul Rahman Saad, Ali Yeon Md Shakaff, Mohd Rozailan Mamat, Hazri Desa and M. Karthigayan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Feature vector
- eigenfaces
- eigenvalues
- eigenvector