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Face Recognition by Using FP-ICA Based on Secant Method

  • Cho, Yong-Hyun (School of Computer and Information Comm. Eng., Catholic Univ. of Daegu)
  • Published : 2005.06.01

Abstract

This paper proposes an efficient face recognition using independent component analysis(ICA) derived from the fixed point(FP) algorithm based on secant method. The secant method can exclude the complex computation of differential process from the FP based on Newton method. The proposed ICA has been applied to recognize the 20 Yale face images of $324\times324$ pixels. The experimental results show that the proposed ICA is superior to PCA not only in the restoration performance of basis images but also in the recognition performance of the trained images and the test images. Then negative angle as similarity measures has better recognition ratio than city-block and Euclidean.

Keywords

References

  1. K. I. Diamantaras and S. Y. Kung, Principal Component Neural Networks: Theory and Applications, Adaptive and learning Systems for Signal Processing, Communications, and Control, John Wiley & Sons, Inc., 1996
  2. S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice Hall, 2ed, London, 1999
  3. J. Karhunen and J. Joutsensalo,'Generation of Principal Component Analysis, Optimization Problems, and Neural Networks,' Neural Networks, Vol. 8, No. 4, pp. 549 562, 1995
  4. P. Comon, 'Independent Component Analysis A New Concept?,' Signal Processing, vol.36, No.3, pp.287 314, Apr. 1994
  5. T. W. Lee, Independent Component Analysis: Theory and Applications, Kluwer Academic Pub., Boston, 1998
  6. J. Karhunen, 'Neural Approaches to Independent Component Analysis and Source Separation,' 4th European Symp., Artificial Neural Network, ESANN96, Burges, Belgium, pp. 249 266, Apr. 1996
  7. A. Hyvaerinen, J. Karhunen, and E. Oja, Independent Component Analysis, John Wiley & Sons, Inc., New York, 2001
  8. A. Hyvaerinen and E. Oja, 'A Fast Fixed Point Algorithms for Independent Component Analysis', Neural Computation, 9(7), pp. 1483 1492, Oct.1997
  9. A. Hyvaerinen, 'Fast & Robust Fixed Point Algorithms for Independent Component Analysis', IEEE Trans. on Neural Networks, Vol. 10, No. 3, pp.626 634, May 1997
  10. A. Hyvaerinen and E. Oja, 'Independent Component Analysis: Algorithms and Applications', Neural Networks, Vol. 13, No. 4 5, pp. 411 430, June 2000
  11. A. Cichocki and R. Unbehauen, 'Robust Neural Networks with On']Line Learning for Blind Identification and Blind Separation of Sources', IEEE Trans. on Circuits & Systems, Vol. 43, No. 11, pp. 894-906, Nov. 1996 https://doi.org/10.1109/81.542280
  12. K. Atkinson, Elementary Numerical Analysis, John Wiley & Sons, Inc., New York, 1993
  13. 'Yale Face Databases,' http://cvc.yale.edu/projects/ yalefaces/ yalefaces.html