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Comparative Analysis of various Illumination Normalization Techniques for Face Recognition

by Tripti Goel, Vijay Nehra, Virendra P.Vishwakarma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 28 - Number 9
Year of Publication: 2011
Authors: Tripti Goel, Vijay Nehra, Virendra P.Vishwakarma
10.5120/3419-4771

Tripti Goel, Vijay Nehra, Virendra P.Vishwakarma . Comparative Analysis of various Illumination Normalization Techniques for Face Recognition. International Journal of Computer Applications. 28, 9 ( August 2011), 1-7. DOI=10.5120/3419-4771

@article{ 10.5120/3419-4771,
author = { Tripti Goel, Vijay Nehra, Virendra P.Vishwakarma },
title = { Comparative Analysis of various Illumination Normalization Techniques for Face Recognition },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 28 },
number = { 9 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume28/number9/3419-4771/ },
doi = { 10.5120/3419-4771 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:14:17.952468+05:30
%A Tripti Goel
%A Vijay Nehra
%A Virendra P.Vishwakarma
%T Comparative Analysis of various Illumination Normalization Techniques for Face Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 28
%N 9
%P 1-7
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The change in facial appearance due to illumination variation degrades face recognition systems performance considerably. In this paper, various states of art illumination normalization techniques have been explained and compared. The classification of the image recognition has been done using artificial neural networks (ANN). We have compared four illumination normalization methods which are (1) discrete cosine transform (DCT) with rescaling of low frequency coefficients (2) discrete cosine transform (DCT) with discarding of low frequency coefficients (3) homomorphic filtering (HF) (4) gamma intensity correction (GIC). These methods are evaluated and compared on Yale and Yale B Faces databases.

References
  1. Proceeding of the International Conferences on the Automatic Face and Gesture Recognition, 1995-1998
  2. Proceeding of the International Conferences on the Audio and Video Based Person Authentication, 199-1998.
  3. W. ZHAO, R. CHELLAPPA, P. J. PHILLIPS AND AROSENFELD, Face Recognition: A Literature Survey, ACM Computing Surveys 35 (4) (2003) pp. 399–458.
  4. R.CHELLAPPA, C. L. WILSON AND S. SIROHEY, Human and machine recognition of faces: a survey. Proceedings of IEEE 83 (5) (1995) pp. 705–740.
  5. P.N. BELHUMEUR AND D. J. KRIEGMAN, What is the set of images of an object under all possible illumination conditions. International Journal of Computer Vision 28 (3) (1998) pp. 245–260.
  6. S.Z LI AND A. K. JAIN, Handbook of Face Recognition, Springer, 2005.
  7. X. ZOU, J. KITTLER AND K. MESSER, Illumination Invariant Face Recognition: A Survey, in: Proceedings of IEEE International Conference on Biometric: Theory, Application and Systems (2007), pp. 1–8.
  8. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, “Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection,” IEEE Trans. on Patt. Ana. and Mach. Intell., vol. 19, no. 7, pp. 711-720, 1997.
  9. T. Cootes, G. Edwards, and C. Taylor, “Active appearance models,” IEEE Trans. on Patt. Ana. and Mach. Intell., vol. 23, no. 6, pp. 681-685, 2001.
  10. M. TURK AND A. PENTLAND, Eigenfaces for Recognition, J. Cognitive Neuroscience, 3 (1) (1991) pp. 71–96.
  11. Y. Adini, Y. Moses, and S. Ullman, “Face recognition: the problem of compensating for changes in illumination direction,” IEEE Trans. PatternAnal. Mach. Intell., vol. 19, no. 7, pp. 721–732, Jul. 1997.
  12. K. DELAC, M. GRGIC AND S. GRGIC, Independent Comparative Study of PCA, ICA, and LDA on the FERET Data Set, International Journal of Imaging Systems and Technology, 15 (5) (2006) pp. 252–260
  13. S. Shan, W. Gao, B. Cao and D. Zhao, "Illumination Normalization for Robust Face Recognition Against Varying Lighting Conditions", Proc. IEEE Workshop on AMFG, pp. 157-164, 2003.
  14. Bruce A. Draper, Kyungim Baek, Marian Stewart Bartlett, “Recognizing faces with PCA and ICA”, Computer vision and Image Understanding 91 (2003) 115-137
  15. T. Ahonen, A. Hadid, and M. Pietikainen, “Face Description with Local Binary Patterns: Application to Face Recognition”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 12, pp. 2037-2041, Dec 2006
  16. R.C. Gonzalez, R.E. Woods, "Digital Image Processing", Prentice Hall, Upper Saddle River, NJ, 2002
  17. Z. M. Hafed and M. D. Levine, “Face recognition using the discrete cosine transform,” Int. J. Comput. Vis., vol. 43, no. 3, pp. 167–188, 2001.
  18. Virendra. Vishwakarma, Sujata Pandey and M. N. Gupta,” An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients”, Journal of Computing and Information Technology - CIT 18, 2010, 1, 53–67
  19. Weilong Chen, Meng Joo Er, and Shiqian Wu,” Illumination Compensation and Normalization for Robust Face Recognition Using Discrete Cosine Transform in Logarithm Domain”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 2, APRIL 2006
  20. K. Delac, M. Grgic, T. Kos, “Sub-Image Homomorphic Filtering Technique for Improving Facial Identification under Difficult Illumination Conditions”, International Conference on Systems, Signals and Image Processing (IWSSIP’06), September 21-23, 2006. Budapest, Hungary
  21. YALE FACE DATABASE B, http://cvc.yale.edu/projects/yalefacesB/yalefacesB.html, 2001.
  22. Shahrin Azuan Nazeer, Nazaruddin Omar And Marzuki Khalid,“Face Recognition System Using Artificial Neural Networks Approach”, IEEE - ICSCN 2007, MIT Campus, Anna University, Chennai, India. Feb. 22-24, 2007. Pp.420-425.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete cosine transform (DCT) homomorphic filtering (HF) gamma intensity correction (GIC) artificial neural networks (ANN)

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