CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Wavelet based Artificial Light Receptor � A feature extraction model for face recognition

Published on February 2012 by Kabeer V.
journal_cover_thumbnail

International Conference on Advances in Computational Techniques
Foundation of Computer Science USA
ICACT2011 - Number 2
February 2012
Authors: Kabeer V.
366efb37-d01a-4753-bef8-0c74442dc853

Kabeer V. . Wavelet based Artificial Light Receptor � A feature extraction model for face recognition. International Conference on Advances in Computational Techniques. ICACT2011, 2 (February 2012), 1-5.

@article{
author = { Kabeer V. },
title = { Wavelet based Artificial Light Receptor � A feature extraction model for face recognition },
journal = { International Conference on Advances in Computational Techniques },
issue_date = { February 2012 },
volume = { ICACT2011 },
number = { 2 },
month = { February },
year = { 2012 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/icact2011/number2/4774-1107/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Computational Techniques
%A Kabeer V.
%T Wavelet based Artificial Light Receptor � A feature extraction model for face recognition
%J International Conference on Advances in Computational Techniques
%@ 0975-8887
%V ICACT2011
%N 2
%P 1-5
%D 2012
%I International Journal of Computer Applications
Abstract

This paper presents a novel biologically inspired and wavelet based model for extracting features of faces from face images. The biological knowledge about the distribution of light receptors, cones and rods, over the surface of the retina, and the way they are associated with the nerve ends for pattern vision forms the basis for the design of this model. A combination of classical wavelet decomposition and wavelet packet decomposition is used for simulating the functional model of cones and rods in pattern vision. The paper also describes the experiments performed for face recognition using the features extracted on the AT&T face database containing 400 face images of 40 different individuals. In the recognition stage we used k-Nearest Neighbour classifier. A feature vector of size 40 is formed for face images of each person and recognition accuracy is computed using k-NN classifier.

References
  1. W. Zhao, R. Chellappa, P.J Philips and A. Rosenfeld, “Face Recognition: A Literature Survey”, ACM Computing Surveys, Vol.35 (4), 399-458, Dec.2003
  2. Ming-Hsuan Yang, David J Kriegman and Narendra Ahuja, “Detecting faces in Images: A Survey”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.24 (1), 34-58, Jan.2002.
  3. M.A. Grudin, “On internal representation of face recognition systems”, Pattern Recognition, Vol.33 (7), 1161-1177, 2000.
  4. J. Daugman, “Face detection: A survey”, Computer Vision and Image Understanding, Vol.83 (3), 236-274, Sept. 2001.
  5. Stan Z. Li, Anil K. Jain, Handbook of Face Recognition, Springer, 2004.
  6. J. Haddadnia and M. Ahmadi, “N-feature neural network human face recognition”, Image and Vision Computing, Vol.22, 1071-1082, 2004.
  7. J. Haddadnia , M. Ahmadi, K Faez, “An Efficient Method for Recognition of Human face using high order Pseudo Zernike Moment Invariant”, The 5th IEEE International Conference on Automatic Face and Gesture Recognition, Washington, DC,USA, 315-32, May 20-21,2000.
  8. J. Wang, T. Tan, ‘A new face detection method based on shape information’, Pattern Recognition Letter, Vol.21, pp.463-471, 2000.
  9. M. Turk, A. Pentland, Eigenfaces for Recognition, Journal of Cognitive Neurosicence, Vol. 3, No. 1, pp. 71-86, 1991.
  10. H. Moon, P.J. Phillips, Computational and Performance aspects of PCA-based Face Recognition Algorithms, Perception, Vol. 30, pp. 303-321, 2001.
  11. M.S. Bartlett, J.R. Movellan, T.J. Sejnowski, Face Recognition by Independent Component Analysis, IEEE Trans. on Neural Networks, Vol. 13, No. 6, pp. 1450-1464, November 2002.
  12. K. Etemad, R. Chellappa, Discriminant Analysis for Recognition of Human Face Images, Journal of the Optical Society of America A, Vol. 14, No. 8, pp. 1724-1733, August 1997.
  13. C. Liu, H. Wechsler, Evolutionary Pursuit and Its Application to Face Recognition, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 22, No. 6, pp. 570-582, June 2000.
  14. L. Wiskott, J.-M. Fellous, N. Krueuger, C. von der Malsburg, Face Recognition by Elastic Bunch Graph Matching, Chapter 11 in Intelligent Biometric Techniques in Fingerprint and Face Recognition, eds. L.C. Jain et al., CRC Press, pp. 355-396, 1999.
  15. M.-H. Yang, Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using Kernel Methods, Proc. of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, 20-21 May 2002, Washington D.C., USA, pp. 215-220 , 2002.
  16. Kadyrov, M. Petrou, The Trace Transform and Its Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 8, pp. 811-828, August 2001.
  17. T.F. Cootes, K. Walker, C.J. Taylor, View-Based Active Appearance Models, Proc. of the IEEE International Conference on Automatic Face and Gesture Recognition, 26-30 March 2000, Grenoble, France, pp. 227-232, 2000.
  18. A.V. Nefian, M.H. Hayes, Maximum likelihood training of the embedded HMM for face detection and recognition, Proc. of the IEEE International Conference on Image Processing, ICIP 2000, Vol. 1, 10-13 September 2000, Vancouver, BC, Canada, pp. 33-36
  19. G. Guo, S.Z. Li, K. Chan, Face Recognition by Support Vector Machines, Proc. of the IEEE International Conference on Automatic Face and Gesture Recognition, 26-30 March 2000, Grenoble, France, pp. 196-201 , 2000.
  20. Mallat S, “Multifrequencies Channel Decompositionsof Images and Wavelets Models”, IEEE Transactions on Acoustics, Speech and Signal Processing, 37(12), 1989.
  21. Daubechies, “The Wavelet Transform, Time-Frequency Localization and Signal Analysis”, IEEE Transactions on Information Theory, 36(5), 961-1005, 1990.
  22. Christophe Garcia, Giorgos Zikos& Giorgos Tziritas, “A Wavelet-based Framework for Face Recognition”, ICS – Foundation for Research and Technology-Hellas, FORTH, 2000.
  23. J.T. Tou & R.C Gonzalez, Pattern Recognition Principles ( Addison Wesley, London, 1974).
  24. Sankar K. Pal & Sushmitha Mitra, Neuro-fuzzy Pattern Recognition – Methods in Soft Computing ( John Wiley & Sons, Inc., 1999).
  25. M. Friedman, A. Kandel, Introduction to Pattern Recognition – Statistical, Structural, Neural and Fuzzy Logic Approac, (World Scientific, 1999).
  26. V. Kabeer & N. K. Narayanan, Face Recognition using Wavelet based Feature parameter and K –NN Classifier, Proceedings Kerala Science Congress, Kannur, pp-887-888, January 2007.
  27. Jaideva C. Goswami & Andrew K. Chan, Fundamentals of Wavelets-Theory, Algorithms and Applications, Wiley Series, 1999.
  28. Rafael C Gonzales & Richard E. Woods, Digital Image Processing, PE, 2002.
  29. Chanda & D. Dutta Majumder, Digital Image Processing and Analysis,PHI, 2000.
  30. Raghuveer M.Rao & Ajith S. Bopardikar, Wavelet Transforms – Introduction to Theory and Applications, PE, 1998.
  31. Michael W. Frazier, An introduction to Wavelets through Linear Algebra, Springer, 1999.
  32. V. Kabeer & N. K. Narayanan, Face Recognition using Wavelet Hybrid Features and K–NN Classifier, Proceedings IEEE ACVIT-07, Aurangabad,, Maharashtra, India., pp 738-746, Nov. 2007.
  33. V. Kabeer & N K Narayanan, Wavelet based Artificial Light Receptor Model for Human Face Recognition, International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP), World Scientific, No.5., 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Face recognition Image analysis Wavelet feature extraction Pattern recognition k-NN Classifier