FACE RECOGNITION USING ARTIFICIAL NEURAL NETWORK

Authors

  • Sentayehu Endeshaw
  • Kumudha Raimond

Abstract

Face recognition (FR) is one of the biometric methods to identifY the individuals by the features of face. Two Face Recognition Systems (FRS) based on Artificial Neural Network (ANN) have been proposed in this paper based on feature extraction techniques. In the first system, Principal Component Analysis (PCA) has been used to extract the features from face images and classify them using ANN. In the second
system, combination of Gabor Filter (GF) and PCA have been used for feature extraction and ANN for classification. The influence of different ANN parameters also has been studied in this work. Experiments have been ca"ied out by using Olivetti Research Laboratory (ORL) face database. The results confirmed the feasibility of the methodologies
followed in this work. Further, the systems performed very efficiently when subjected to new unseen images with afalse rejection rate o/0% during testing.

Downloads

Published

2023-01-31

How to Cite

Endeshaw, S., & Raimond, K. . (2023). FACE RECOGNITION USING ARTIFICIAL NEURAL NETWORK. Zede Journal of Ethiopian Engineers and Architects, 25, 43–52. Retrieved from http://ejol.aau.edu.et/index.php/ZEDE/article/view/6579

Issue

Vol. 25 (2008): Zede: Journal of Ethiopian Engineers and Architects

Section

Articles