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Comparison of PCA and MPCA with Different Databases for Face Recognition
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 43 - Number 17 |
| Year of Publication: 2012 |
| Authors: Ambika.d, Arathy.b, Srinivasa Perumal.r |
10.5120/6198-8730
|
Ambika.d, Arathy.b, Srinivasa Perumal.r . Comparison of PCA and MPCA with Different Databases for Face Recognition. International Journal of Computer Applications. 43, 17 ( April 2012), 30-34. DOI=10.5120/6198-8730
Abstract
Face recognition is one of the Biometric characteristics for person identification. In this paper, Face recognition is done using two feature extraction techniques PCA (Principal Component Analysis) and MPCA (Modular Principal Component Analysis). PCA is a linear projection method in which dimensionality reduction is applied to the original image space. MPCA is an improved version of PCA in which each image (Face image) is divided into number of sub-block image and then PCA is applied for each sub-block image. The experimental result shows the accuracy of PCA and MPCA for different database images.
References
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