ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.047
Automatic Face Recognition using Principal Component Analysis and Neural Network
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
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
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.