Image segmentation through gabor-based neural networks

J. Mario Aguilar, José L. Contreras-Vidal

Research output: Contribution to journalConference article

1 Scopus citations

Abstract

An image segmentation system based on known cortical interactions and topography is presented. First, a space variant retinal-like representation of the image is obtained not only to provide with spatial focusing but also to reduce the computational load. Next, a layer of receptive fields for feature extraction was evolved from a set of Gabor functions with multiple orientational characteristics. Shunting competitive interactions among different features eliminate local ambiguities. Long-range interactions among "winning" cells, sharing similar orientation preferences, but with possible different spatial scales, are used to form a congruent description of the visual scene taking into account spatial context. The output of this layer js used to partition the image into emergent segments. Encouraging results of MRI images processing are presented.

Original languageEnglish (US)
Pages (from-to)44-51
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1709
DOIs
StatePublished - Sep 16 1992
EventApplications of Artificial Neural Networks III 1992 - Orlando, United States
Duration: Apr 20 1992 → …

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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