Advertisement

Iterative Tuning of Simple Cells for Contrast Invariant Edge Enhancement

  • Marina Kolesnik
  • Alexander Barlit
  • Evgeny Zubkov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

This work describes a novel model for orientation tuning of simple cells in V1. The model has been inspired by a regular structure of simple cells in the visual primary cortex of mammals. Two new features distinguish the model: the iterative processing of visual inputs; and amplification of tuned responses of spatially close simple cells. Results show that after several iterations the processing converges to a stable solution while making edge enhancement largely contrast independent. The model suppresses weak edges in the vicinity of contrastive luminance changes but enhances isolated low-intensity changes. We demonstrate the capabilities of the model by processing synthetic as well as natural images.

Keywords

Ganglion Cell Visual Input Lateral Geniculate Nucleus Simple Cell Perceptual Grouping 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hubel, D., H., Wiesel, T., N.: Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. Journal of Psychology, 160:106–154, 1962.Google Scholar
  2. 2.
    Hubel, D., H., Wiesel, T., N.: Integrative action in the cat’s lateral geniculate body. Journal of Psychology, 155:385–398, 1961.Google Scholar
  3. 3.
    Kuffler, S., W.: Discharge patterns and functional organization of mammalian retina. Journal of Neurophysiology, 16:37–68, 1953.Google Scholar
  4. 4.
    Hubel, D., H., Wiesel, T., N.: Sequence regularity and geometry of orientation columns in the monkey striate cortex. Journal of Comparative Neurology, 158:267–294, 1974.CrossRefGoogle Scholar
  5. 5.
    Hubel, D., H., Wiesel, T., N.: Functional architecture of macaque monkey visual cortex. Proceedings of the Royal Cosiety of London, B, 198:1–59, 1977.Google Scholar
  6. 6.
    Enroth-Cugell, C., Robson, J., G.: The contrast sensitivity of retinal ganglion cells of the cat. Journal of Physiology, 187:517–552, 1965.Google Scholar
  7. 7.
    Croner, L., J., Kaplan, E.: Receptive fields of P and M ganglion cells across the primate retina. Vision research, 35:7–24, 1995.CrossRefGoogle Scholar
  8. 8.
    Ferster, D.: The synaptic inputs to simple cells in the cat visual cortex. In: D. Lam and G. Gilbert (eds.): Neural mechanisms of visual perception, Ch. 3, Portfolio Publ. Co, The Woodlands, Texas:63–85, 1989.Google Scholar
  9. 9.
    Pessoa, L., Mingolla, E., Neumann, H.: A contrast-and luminance-driven multiscale network model of brightness perception. Vision Research, 35:2201–2223, 1995.CrossRefGoogle Scholar
  10. 10.
    Neumann, H., Pessoa, L., Hansen, Th.: Interaction of ON and OFF pathways for visual contrast measurement. Biological Cybernetics, 81:515–532, 1999.CrossRefGoogle Scholar
  11. 11.
    Hansen, Th., Baratoff, G., Neumann, H.: A simple cell model with dominating opponent inhibition for robust contrast detection. Kognitionswissenschaft, 9:93–100, 2000.Google Scholar
  12. 12.
    Silito, A., M., Jones, H., E., Gerstein, G., L., West, D., C.: Feature-linked synchronization of thalamic relay cell firing induced by feedback from the visual cortex. Nature, 369:479–482,1994.CrossRefGoogle Scholar
  13. 13.
    Grossberg, S., Raizada, R., D., S.: Contrast-sensitive perceptual grouping and object-based attention in the laminar circuits of primary visual cortex. CAS/CNS TR-99-008, Boston University:1–35, 1999.Google Scholar
  14. 14.
    Gilbert, C., D., Wiesel, T., N.: The influence of contextual stimuli on the orientation selectivity of cells in primary visual cortex of the cat. Vision research, 30:1689–1701, 1990.CrossRefGoogle Scholar
  15. 15.
    Grossberg, S., Mingolla, E., Ross, W., D. Visual brain and visual perception: how does the cortex do perceptual grouping? Trends in Neurosciences, 20:106–111, 1997.CrossRefGoogle Scholar
  16. 16.
    Hansen, Th., Neumann, H. A model of V1 visual contrast processing utilizing long-range connections and recurrent interactions. In Proc. of the International Conference on Artificial Neural Networks, Edinburgh, UK, Sept. 7-10:61–66, 1999.Google Scholar
  17. 17.
    Borg-Graham, L. J., Monier, C., Fregnac, Y.: Visual input invokes transient and strong shunting inhibition in visual cortical neurons. Nature, 393, (1998) 369–373.CrossRefGoogle Scholar
  18. 18.
    Sclar, G., Freeman, R.: Orientation selectivity in the cat’s striate cortex is invariant with stimulus contrast. Experimental Brain research, 46, (1982) 457–461.CrossRefGoogle Scholar
  19. 19.
    Skottun, B., Bradley, A., Sclar, G., Ohzawa, I., Freeman, R.: The effects of contrast on visual orientation and spatial frequency discrimination: a comparison of single cells and behavior. Journal of Neurophysiology, 57:773–786, 1987.Google Scholar
  20. 20.
    Pfeifer, R., and Scheier, C: Understanding intelligence. Cambridge, Mass.: MIT Press, 1999.Google Scholar
  21. 21.
    Pfeifer, R.: On the role of morphology and materials in adaptive behaviour. In: J.-A. Meyer, A. Berthoz, D. Floreano, H. Roitblat, and S.W. Wilson (eds.). From animals to animats 6. Proc. of the 6th Int. Conf. on Simulation of Adaptive Behaviour: 23–32, 2000.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Marina Kolesnik
  • Alexander Barlit
    • 1
  • Evgeny Zubkov
    • 1
  1. 1.Fraunhofer Institute for Media CommunicationSankt-AugustinGermany

Personalised recommendations