Face Recognition Using Principal Component Analysis in MATLAB

Prabhjot Singh¹ , Anjana Sharma²

Section:Research Paper, Product Type: Isroset-Journal
Vol.3 , Issue.1 , pp.1-5, Jan-2015

Online published on Feb 28, 2015

Copyright © Prabhjot Singh , Anjana Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
The paper present an semi-automated program for human face recognition. A self prepared database of different faces is used. Task of removing background from the image is a challenge but on the other hand by implementing Viola-Jones face detection algorithm and by Principal Component analysis it is possible. An application of system can be real time implementation of face recognition system. A robust and reliable form of recognition can be done by using Principal Component analysis. In the process Eigen faces or Eigen values are selected by PCA calculating the nearest face or value and then displaying result. This biometric system has real time application as used in attendance systems.

Key-Words / Index Term :
Eigenface, Eigenvalues, Detection, PCA, Recognition

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