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A Model of Contour Integration in Early Visual Cortex

  • T. Nathan Mundhenk
  • Laurent Itti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

We have created an algorithm to integrate contour elements and find the salience value of them. The algorithm consists of basic long-range orientation specific neural connections as well as a novel group suppression gain control and a fast plasticity term to explain interaction beyond a neurons normal size range. Integration is executed as a series of convolutions on 12 orientation filtered images augmented by the nonlinear fast plasticity and group suppression terms. Testing done on a large number of artificially generated Gabor element contour images shows that the algorithm is effective at finding contour elements within parameters similar to that of human subjects. Testing of real world images yields reasonable results and shows that the algorithm has strong potential for use as an addition to our already existent vision saliency algorithm.

Keywords

Contour Integration Salient Point Temporal Synchronization Gabor Patch Real World Image 
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

  • T. Nathan Mundhenk
    • 1
  • Laurent Itti
    • 1
  1. 1.Computer Science DepartmentUniversity of Southern CaliforniaLos AnglesUSA

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