CFP last date
22 July 2024
Call for Paper
August Edition
IJCA solicits high quality original research papers for the upcoming August edition of the journal. The last date of research paper submission is 22 July 2024

Submit your paper
Know more
Reseach Article

Article:A Comparative study of Face Recognition with Principal Component Analysis and Cross-Correlation Technique

by Srinivasulu Asadi, Dr.Ch.D.V.Subba Rao, V.Saikrishna
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 10 - Number 8
Year of Publication: 2010
Authors: Srinivasulu Asadi, Dr.Ch.D.V.Subba Rao, V.Saikrishna
10.5120/1502-2019

Srinivasulu Asadi, Dr.Ch.D.V.Subba Rao, V.Saikrishna . Article:A Comparative study of Face Recognition with Principal Component Analysis and Cross-Correlation Technique. International Journal of Computer Applications. 10, 8 ( November 2010), 17-21. DOI=10.5120/1502-2019

@article{ 10.5120/1502-2019,
author = { Srinivasulu Asadi, Dr.Ch.D.V.Subba Rao, V.Saikrishna },
title = { Article:A Comparative study of Face Recognition with Principal Component Analysis and Cross-Correlation Technique },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 10 },
number = { 8 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume10/number8/1502-2019/ },
doi = { 10.5120/1502-2019 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:59:11.113201+05:30
%A Srinivasulu Asadi
%A Dr.Ch.D.V.Subba Rao
%A V.Saikrishna
%T Article:A Comparative study of Face Recognition with Principal Component Analysis and Cross-Correlation Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 10
%N 8
%P 17-21
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automated face recognition has become a major field of interest. Face recognition algorithms are used in a wide range of applications viz., security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different face recognition techniques by considering different test samples. The experimentation involved the use of Eigen faces and PCA (Principal Component Analysis). Another method based on Cross-Correlation in spectral domain has also been implemented and tested. Recognition rate of 90% was achieved for the above mentioned face recognition techniques.

References
  1. Jackson, J. E., “A Users Guide to Principal Components”, John Wiley and Sons, pp. 1-25, 1991.
  2. Kyungnam Kim, “Face Recognition using principal component analysis”, USA, June 2000.
  3. Geof Givens, J Ross Beveridge, Bruce A. Draper and David Bolme,” A Statistical Assessment of Subject Factors in the PCA Recognition of Human Faces”, April 2003.
  4. Bruce A. Draper, Kyungim Baek, Marian Stewart Bartlett and J. Ross Beveridge,” Recognizing Faces with PCA and ICA”, 2002.
  5. J. Ross Beveridge, Kai She and Bruce A. Draper and Geof H. Givens”A Nonparametric Statistical Comparison of Principal Component and Linear Discriminant Subspaces for Face Recognition”.
  6. Matthew Turk, Alex Pentland, “Eigen faces for Recognition” Vision and Modeling Group, the Media Laboratory, Massachusetts Institute of Technology; September 1990.
  7. Imola K. Fodor,” A survey of dimension reduction techniques”, June 2002
  8. W. Yambor, B. Draper and R. Beveridge, Analyzing PCA-based Face Recognition Algorithms: “Eigen vector Selection and Distance Measures”, July 2000
  9. Christopher James Cobb, “Face Recognition Project”, December, 2001.
  10. Geof H. Givens, J. Ross Beveridge, Bruce A. Draper and David Bolme, “Using A Generalized Linear Mixed Model to Study the Configuration Space of a PCA+LDA Human Face Recognition Algorithm”, April 2003
  11. B.V.K. Vijaya Kumar, “Tutorial survey of composite filter designs for optical correlators,” Appl. Opt. 31, pp. 4773-4801 (1992).
  12. B.V.K. Vijaya Kumar, and D. Casasent, A. Mahalanobis, “Minimum average correlation energy filters,” Appl. Opt. 26, pp. 3633-3630 (1987).
  13. Gonzales, R and Woods R,”Digital Image Processing, 2nd Edition Prentice-Hall Englewood cliffs, NJ, 2002.
  14. Mario’s Savvides and B.V.K .Vijaya Kumar and Pradeep Khosla, “Face verification using correlation filters”, U.S.A.
  15. Greg Dew and Ken Holmlund, “Investigations of Cross-Correlation of and Euclidean Distance Target Matching Techniques in the MPEF environment”.
  16. Beata J Wysocki, Tadeusz A Wysocki “Orthogonal Binary Sequences with Wide Range of Correlation Properties”, Australia.
  17. John W.Fisher III, “Nonlinear Extensions to the Minimum Average Correlation Energy-Filter” University of Florida, 1997.
  18. Ahmet Bahtiyar Gul “Holistic Face recognition by Dimension reduction”, May 2002.
  19. Ilker Atalay, “Face Recognition using Eigen faces”, January 1996.
  20. Mat lab 6.0 “Image Processing Tool Box”.
Index Terms

Computer Science
Information Sciences

Keywords

Face Recognition Principal Component Analysis Cross-Correlation Technique