Face Recognition using Principle Component Analysis for Biometric Security System

Face Recognition using Principle Component Analysis for Biometric Security System

  IJCOT-book-cover
 		 International Journal of Computer & Organization Trends (IJCOT)          
 
© 2013 by IJCOT Journal
Volume-3 Issue-4                           
Year of Publication :  2013
Authors : Raman Kumar, Satnam Singh

Citation

Raman Kumar, Satnam Singh . "Face Recognition using Principle Component Analysis for Biometric Security System" . International Journal of Computer & organization Trends (IJCOT), V3(4):38-40 Jul - Aug 2013, ISSN 2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract

Face recognition issue gained more interest recently due to its various applications and the demand of high security. In this paper two Face Recognition techniques, Eigen-faces commonly called Principal Component Analysis (PCA) and Fisher-faces commonly called Linear Discriminant Analysis (LDA), are considered and implemented using MATLAB. The performance of the two techniques is then compared in facial recognition and detection tasks. The comparisons are done using a facial recognition database of 100 images captured over a range of poses, lighting conditions and occlusions.

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Keywords

PCA, LDA, Fisher face, Eigen face, Eigen value.