Enhanced Face Recognition System Based on Deep CNN
Bendjillali Ridha Ilyas, Mohammed Beladgham, Khaled Merit, Kamline Miloud · 2019
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 Adaptive Histogram Equalization algorithm (AHE), and feature learning for classification. For learning the features followed by classification we used VGG16, ResNet50 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 Resnet50 architecture has achieved a rate of 97, 23% and 98, 38% respectively.