Advertisement

Neural Network Based on Multi-valued Neurons: Application in Image Recognition, Type of Blur and Blur Parameters Identification

  • Igor Aizenberg
  • Naum Aizenberg
  • Constantine Butakoff
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2085)

Abstract

Some important ideas of image recognition using neural network based on multi-valued neurons are being developed in this paper. We are going to discuss the recognition of color images, distortion (blur) types, distortion parameters and recognition of images with distorted training set.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aizenberg N.N., Aizenberg I.N.. Krivosheev G.A. “Multi-Valued Neurons: Learning, Networks, Application to Image Recognition and Extrapolation of Temporal Series”, Lecture Notes in Computer Science, Vol. 930, (J. Mira, F. Sandoval-Eds.), Springer-Verlag, pp. 389–395, 1995.Google Scholar
  2. 2.
    I.N. Aizenberg, N.N. Aizenberg “Pattern Recognition Using Neural Network Based on Multi-Valued Neurons”, Lecture Notes in Computer Sciense, Vol. 1607-II (J. Mira, J.V. Sanches-Andres-Eds.), Springer-Verlag, pp. 383–392, 1999.Google Scholar
  3. 3.
    I.N. Aizenberg, N.N. Aizenberg, J. Vandewalle Multi-Valued and Universal Binary Neurons: Theory, Learning, Applications, Kluwer Academic Publishers, Boston/Dordrecht/London, 2000.Google Scholar
  4. 4.
    I. Aizenberg, N. Aizenberg, C. Butakoff, E. Farberov “Image Recognition on the Neural Network Based on Multi-Valued Neurons”, Proceedings of the 15 th International Conference on Pattern Recognition, Barcelona, Spain September 3-8, 2000, IEEE Computer Society Press, 2, pp. 993–996, 2000.Google Scholar
  5. 5.
    H. Aoki, Y. Kosugi “An Image Storage System Using Complex-Valued Associative Memory”, Proceedings of the 15 th International Conference on Pattern Recognition, Barcelona, Spain September 3-8, 2000, IEEE Computer Society Press, 2, pp. 626–629, 2000.Google Scholar
  6. 6.
    S. Jankowski, A. Lozowski, M. Zurada “Complex-Valued Multistate Neural Associative Memory”, IEEE Trans. on Neural Networks, 7, pp.1491–1496, 1996.CrossRefGoogle Scholar
  7. 7.
    S. Lawrence, C. Lee Giles, Ah Chung Tsoi and A.D. Back “Face Rocognition: A Convolutional Neural-Network Approach”, IEEE Trans. on Neural Networks, 8, pp. 98–113, 1997.CrossRefGoogle Scholar
  8. 8.
    A.V. Oppenheim and S.J. Lim “The Importance of Phase in Signals”, Proceedings IEEE, 69, pp. 529–541, 1981.CrossRefGoogle Scholar
  9. 9.
    O.P. Milyukova “On Justification of Image Model”, SPIE Proceedings, 3348, pp283–289, 1998.CrossRefGoogle Scholar
  10. 10.
    N. Ahmed, K.R. Rao Orthogonal Transforms for Digital Signal Processing, Springer, 1975.Google Scholar
  11. 11.
    W.K. Pratt Digital Image Processing, John Wiley & Sons, N.Y., 1978.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Igor Aizenberg
    • 1
  • Naum Aizenberg
    • 1
  • Constantine Butakoff
    • 1
  1. 1.Neural Networks Technologies Ltd. (Israel) NNT Ltd.Ramat-GanIsrael

Personalised recommendations