WCSE 2017
ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.047

Automatic Face Recognition using Principal Component Analysis and Neural Network

Mirabeau Nguela, Zenghui Wang, Yanxia Sun

Abstract— Automatic face recognition is a very important research area in computer science since it has been widely used in security systems. It has drawn a lot of attention in the recent ten years from the scientific communities with the aim to provide highly intelligent human-machine interaction with high performance. This paper proposes an automatic face recognition method that encompasses a reduction of significant variable features using the principal components analysis and classification method through Neural Network. The experimental results obtained show an improvement in term of recognition rate compared with the existing method.

Index Terms— Principal component analysis, neural network, eigenvalues and eigenvectors, covariance matrix, feed forward network

Mirabeau Nguela, Zenghui Wang
Department of Electrical and Mining Engineering, University of South Africa, AFRICA
Yanxia Sun
Department of Electrical and Electronic Engineering Science, University of Johannesburg, SOUTH AFRICA


Cite: Mirabeau Nguela, Zenghui Wang, Yanxia Sun, "Automatic Face Recognition using Principal Component Analysis and Neural Network," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 272-277, Beijing, 25-27 June, 2017.