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Face Recognition based on GSVD

by Nidhal Khdhair El Abbadi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 12
Year of Publication: 2015
Authors: Nidhal Khdhair El Abbadi
10.5120/20028-1543

Nidhal Khdhair El Abbadi . Face Recognition based on GSVD. International Journal of Computer Applications. 114, 12 ( March 2015), 9-12. DOI=10.5120/20028-1543

@article{ 10.5120/20028-1543,
author = { Nidhal Khdhair El Abbadi },
title = { Face Recognition based on GSVD },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 12 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number12/20028-1543/ },
doi = { 10.5120/20028-1543 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:52:33.294856+05:30
%A Nidhal Khdhair El Abbadi
%T Face Recognition based on GSVD
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 12
%P 9-12
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The task of face recognition has been actively researched in recent years because of its many applications in various domains. This study suggested new and novel method to matching the input face image with face images in database based on GSVD. Euclidian distance for the norm of two factors resulted from GSVD of each pair of images was determined. When the distance less or equal to specific threshold we decide the two images matched. The accuracy of this proposed algorithm was high comparing with other algorithms and it reached up to 97. 21%. The algorithm tested with images from ORL database and Indian face database.

References
  1. Sakthivel, S. and M. Rajaram, 2011. Improving the performance of machine learning based multi attribute face recognition algorithm using wavelet based image decomposition technique. J. Comput. Sci. , 7: 366-373. DOI: 10. 3844/jcssp. 2011. 366. 373.
  2. Rani, J. S. , 2012. Face recognition using hybrid approach. Int. J. Image Graphics, 12: 1-27. DOI: 10. 1142/S0219467812500052.
  3. Zhang, Y. , B. Yu and H. M. Gu, 2012. Face recognition using curvelet based two dimensional principle component analysis. Int. J. Patt. Recogn. Artif. Intell. , 26: 1-13. DOI: 10. 1142/S0218001412560095.
  4. Wan, M. , G. Yang, Z. Lai and Z. Jin, 2010. Feature extraction based on fuzzy local discriminate embedding with applications to face recognition. IET Computer Vision, 5: 301. DOI: 10. 1049/iet-cvi. 2011. 0028.
  5. Kumar, M. S. S. , R. Swami and M. Karuppiah, 2011. An improved face recognition technique based on modular LPCA approach. J. Comput. Sci. , 7: 1900-1907. DOI: 10. 3844/jcssp. 2011. 1900. 1907.
  6. Noushath, S. , A. Rao and G. H. Kumar, 2007. SVD based algorithms for robust face and object recognition in robot vision applications. Proceedings of the 24th International Symposium on automation and Robotics in Construction, (ISA 07), pp: 473-477.
Index Terms

Computer Science
Information Sciences

Keywords

Face Matching Face Recognition GSVD Biometrics

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