Research Article | OPEN ACCESS
Investigation of Feature Selection Techniques for Face Recognition Using Feature Fusion Model
1N. Vijaya Kumar and 2M.S. Irfan Ahmed
1Research and Development Centre, Bharathiar University,
2Sri Krishna Institutions, Sri Krishna College of Engineering and Technology, Coimbatore, India
Research Journal of Applied Sciences, Engineering and Technology 2015 1:40-47
Received: January ‎8, ‎2015 | Accepted: February ‎27, ‎2015 | Published: September 05, 2015
Abstract
This study investigates various feature selection techniques for face recognition. Biometric based authentication system protects access to resources and has gained importance, because of their reliable, invariant and discriminating features. An automated biometric system is based on physiological or behavioral human characteristics for protected access. Biometric trait such as palmprint, iris, hand, voice, face fingerprint, or signature is used to authenticate a person's claim. Of the biometrics, face recognition is gaining popularity due to its simple method of capturing the image using cameras. However the number of features generated is high leading to higher computation time. Using feature selection technique it is shown that recognition rate improves.
Keywords:
Biometrics, Correlation-based Feature Selection (CFS), face recognition, k Nearest Neighbor (kNN), Mutual Information (MI) , Naive Bayes (NB) , ORL face database,
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Competing interests
The authors have no competing interests.
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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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