CFP last date
22 April 2024
Reseach Article

Comparison of PCA and MPCA with Different Databases for Face Recognition

by Ambika.d, Arathy.b, Srinivasa Perumal.r
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

@article{ 10.5120/6198-8730,
author = { Ambika.d, Arathy.b, Srinivasa Perumal.r },
title = { Comparison of PCA and MPCA with Different Databases for Face Recognition },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 17 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number17/6198-8730/ },
doi = { 10.5120/6198-8730 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:33:41.711319+05:30
%A Ambika.d
%A Arathy.b
%A Srinivasa Perumal.r
%T Comparison of PCA and MPCA with Different Databases for Face Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 17
%P 30-34
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
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
  1. Chellappa, R. , Wilson, C. L. , Sirohey, S. , 1995. Human and machine recognition of faces: A survey. Proc. IEEE 83 (5), 705–740.
  2. Kirby and L. Sirovich "Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces", IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol-12, No-1, January 1990.
  3. M. Turk and A. Pentland, "Face Recognition using ```Eigen Faces", Proc. IEEE Conf. on Computer Vision and Pattern Recognition. Pages 586-591, 1991.
  4. Sheifali Gupta et al. "A Bespoke Approach for Face Recognition using PCA" International Journal on Computer Science and Engineering (IJCSE) , Vol. 02, No. 02, 2010 155-158.
  5. Rajkiran Gottumukkal, Vijayan K. Asari, "An improved face recognition technique based on modular PCA approach", Pattern Recognition Letters 25(2004) 429-436.
  6. Chengmao Han, "Modular PCA Face Recognition based on Weighted Average ", CCSC journal, November 2009, Vol-3, No. 11.
  7. Kiran Jain & Sukhvir Singh, "Performance Evaluation Of Face Recognition Using PCA", International Journal Of Information Technology and Knowledge Management, July-December 2011, Volume 4, No. 2, pp. 427-430.
  8. Stan Z. Li & Anil K. Jain, "Handbook of Face Recognition", second edition. Springer, 2011.
  9. Rabia Jafri and Hamid R. Arabnia, "A Survey of Face Recognition Techniques", Journal Of Information Processing Systems, Vol. 5, No. 2, June 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Pca Modular Pca Face Recognition Eigen Faces