Abdullah, Abdulqadir Ismail and Al-Dabagh, Mustafa Zuhaer Nayef and Alhabib, Mustafa H. Mohammed (2018) Independent Component Analysis and Support Vector Neural Network for Face Recognition. International Journal of Applied Engineering Research, 13 (7). pp. 4802-4806. ISSN 0973-4562
![[thumbnail of Research Article]](https://eprints.cihanuniversity.edu.iq/style/images/fileicons/text.png)
Article_IJAER_13-11-2018.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (493kB)
Abstract
With increasing rate of security threats in last decade, attentions toward the field of face detection and recognition have increased rapidly. Many face recognition algorithms have been introduced and most of them are focused on increasing the accuracy rate of the recognition system. In this paper, face recognition system using Independent Component Analysis (ICA) for features extraction and Support Vector Neural Network (SVNN) for classification is suggested. Also, a comparison between each of SVNN, Support Vector Machine (SVM) and Artificial Neural Networks (ANNs) is given as a demonstration of the reliability of the proposed method. The experiments are implemented using Yale databases and the results reveal that the suggested method has a classification accuracy of % 95.238, which is higher than the results of (ICA+SVM) and (ICA+ANNs) methods, respectively
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Face Recognition, ICA, SVM, ANN. |
Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics |
Divisions: | Department of Accounting > Research papers |
Depositing User: | ePrints Depositor |
Date Deposited: | 08 Oct 2024 06:41 |
Last Modified: | 08 Oct 2024 06:41 |
URI: | https://eprints.cihanuniversity.edu.iq/id/eprint/1199 |