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- Title
Feature extraction and classification using deep convolutional neural networks, PCA and SVC for face recognition.
- Authors
Benkaddour, Mohammed Kamel; Bounoua, Abdennacer
- Abstract
Recently, the facial recognition has aroused the interest of the scientific community, this technique of biometric that is effective, non-intrusive and contactless has taken an increasingly important part in the field of research. This paper proposes a face recognition and classification method based on deep learning, in particular Convolutional Neural Network (CNN), which are incredibly a powerful tools that have found great success in image classification and pattern recognition. In this work, the approach to this task is based on the Convolutional Neural Network (CNN) as a powerful feature extraction followed by Support Vector Machines (SVM) as a high classifier. To reduce the dimension of these features, a principal component analysis (PCA) technique is employed. We conduct an extensive evaluation of our methods on the FERET dataset. The results obtained showed that the proposed method CNN combine with PCA and Svc solution provide a significant improvement in performance and enhance the recognition accuracy.
- Publication
Traitement du Signal, 2017, Vol 34, Issue 1/2, p77
- ISSN
0765-0019
- Publication type
Academic Journal
- DOI
10.3166/TS.34.77-91