Performance Comparison of Eigen-faces vs. Fisher-faces for Face Recognition

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

Authors and Affiliations

Raman Kumar , Satnam Singh

Keywords

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  • EP ID EP136322
  • DOI -
  • Views 109
  • Downloads 0

How To Cite

Raman Kumar, Satnam Singh (2013). Performance Comparison of Eigen-faces vs. Fisher-faces for Face Recognition. International Journal of Computer & organization Trends(IJCOT), 3(8), 314-317. https://europub.co.uk./articles/-A-136322