Advertisement

Application of a multilayer discrete-time CNN to deformable models

  • D. L. Vilariño
  • D. Cabello
  • A. Mosquera
  • J. M. Pardo
Neural Networks for Perception
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1240)

Abstract

In this work Cellular Neural Networks are applied to image analysis techniques as a deformable models. To this end the problem is considered based on a discrete-time CNN with cyclic templates and time-variant external inputs. The appropriateness for a VLSI implementation and massively parallel computing of CNNs will permit a considerable improvement in processing speed with respect to the clasical active contours approaches.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    L. O. Chua and L. Yang, “Cellular Neural Networks; Theory and Applications”, IEEE Trans. Circuits Syst. Vol. 35, N. 10, pp 1257–1272, 1988.Google Scholar
  2. [2]
    H. Harrer and J.A. Nossek, “Discrete-Time Cellular Neural Networks”, Int. Journal Circuit Theory and Appls., Vol. 20, pp. 453–467, 1992.Google Scholar
  3. [3]
    H. Harrer, J.A. Nossek and R. Stelzl, “An Analog Implementation of Discrete-Time Cellular Neural Networks”, IEEE Trans. on Neural Networks, Vol 3, N. 3, pp. 466–476, 1992.Google Scholar
  4. [4]
    M.H. ter Brugge, R.J. Krol, J.A.G. Nijhuis and L. Spaanenburg, “Design of Discrete-Time Cellular Neural Networks Based on Mathematical Morphology”, IEEE Int. Work. on Cellular Neural Networks and their Applications, pp. 1–5, 1996.Google Scholar
  5. [5]
    C. Guzelis and S. Karamahmut, “Recurrent Perceptron Learning Algorithm for CNNs with Application to Edge Detection”, IEEE Int. Conf. Neural Networks, pp. 1134–1139,1995.Google Scholar
  6. [6]
    T. Kozek, T. Roska and L.O. Chua, “Genetic Algorithm for CNN template Learning”, IEEE Trans. Circuits Syst., Vol. 40, N∘. 6, pp. 392–402, 1993.Google Scholar
  7. [7]
    R. Tetzlaff, D. Wolf, “A Learning Algorithm for the Dynamics of CNN with Nonlinear Templates-Part I: Discrete-time”, IEEE Int. Work. on Cellular Neural Networks and their Applications, pp.461–467, 1996.Google Scholar
  8. [8]
    H. Harrer, “Multiple Layer Discrete-Time Cellular Neural Networks Using Time-Variant Templates”, IEEE Trans. Circuits Syst. Vol. 40, N. 3, pp. 191–199, 1993.Google Scholar
  9. [9]
    M.H. ter Brugge, L. Spaanenburg, W.J. Jansen and J.A.G. Nijhuis, “Optimizing the Morphological Design of Discrete-Time Cellular Neural Networks”, IEEE Int. Work. on Cellular Neural Networks and their Applications, pp. 339–343, 1996.Google Scholar
  10. [10]
    M. Kass, A. Witkin and D. Terzopulos, “Snakes: Active Contour Models”, Int. Journal of Computer Vision, pp. 321–331, 1988Google Scholar
  11. [11]
    T. McInerney and D. Terzoupoulos, “Deformable Models in Medical Analysis: A Survey”, Medical Image Analysis Journal, Vol. 1, N. 2, pp. 91–108, 1996.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • D. L. Vilariño
    • 1
  • D. Cabello
    • 1
  • A. Mosquera
    • 1
  • J. M. Pardo
    • 1
  1. 1.Departamento de Electrónica y Computation, Facultad de FísicaUniversidad de Santiago de CompostelaSantiago de CompostelaSpain

Personalised recommendations