Author:
Bendjillali Ridha Ilyas,Beladgham Mohammed,Merit Khaled,Taleb-Ahmed Abdelmalik
Abstract
<p><span>In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology. In this research paper, we present a Face Recognition (FR) system divided into three steps: The Viola-Jones face detection algorithm, facial image enhancement using Modified Contrast Limited Adaptive Histogram Equalization algorithm (M-CLAHE), and feature learning for classification. For learning the features followed by classification we used VGG16, ResNet50 and Inception-v3 Convolutional Neural Networks (CNN) architectures for the proposed system. Our experimental work was performed on the Extended Yale B database and CMU PIE face database. Finally, the comparison with the other methods on both databases shows the robustness and effectiveness of the proposed approach. Where the Inception-v3 architecture has achieved a rate of 99, 44% and 99, 89% respectively.</span></p>
Publisher
Institute of Advanced Engineering and Science
Subject
Electrical and Electronic Engineering,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Information Systems,Signal Processing
Cited by
21 articles.
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