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Contour Detection by Synchronization of Integrate-and-Fire Neurons

  • Etienne Hugues
  • Florent Guilleux
  • Olivier Rochel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

We present a biologically inspired spiking neural network which is able to detect contours in grey level images by synchronization of neurons. This network is made of integrate-and-fire neurons, spaced on a triangular network, whose oriented receptive field is constructed by a wavelet which specifically detects edges. The neurons are excitatorily and locally connected between receptive fields that tend to detect the same contour. A contour, if its width is not too large, activates a chain of neurons, with some heterogeneity in the inputs. The capacity of a chain tosync hronize with respect tosuc h heterogeneity is studied. Synchronization on a contour is found to be possible for a sufficiently large width.

Keywords

Receptive Field Contour Integration Grey Level Image Contour Detection Synchronization Property 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Etienne Hugues
    • 1
  • Florent Guilleux
    • 1
  • Olivier Rochel
    • 1
  1. 1.LORIA, Université de Nancy 1Vandoeuvre-lès-NancyFrance

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