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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Towards Face Recognition Using Eigenface
Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070505
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 5, 2016.
Abstract: This paper presents a face recognition system employing eigenface-based approach. The principal objective of this research is to extract feature vectors from images and to reduce the dimension of information. The method is implemented on frontal view facial images of persons to explore a two-dimensional representation of facial images. The system is organized with RMS (Root Mean Square) contrast scaling technique employed for pre-processing the images to adjust with poor lighting conditions. Experiments have been conducted using Carnegie Mellon University database of human faces and University of Essex Computer Vision Research Projects dataset. Experimental results indicate that the proposed eigenface-based approach can classify the faces with accuracy more than 80% in all cases.
Keywords: Eigenvector; Eigenface; RMS Contrast Scaling; Face Recognition
Md. Al-Amin Bhuiyan, “Towards Face Recognition Using Eigenface” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070505
@article{Bhuiyan2016,
title = {Towards Face Recognition Using Eigenface},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070505},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070505},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Md. Al-Amin Bhuiyan}
}
