Edge detection and image segmentation: Two sides of the same coin

Victor Boskovitz, Hugo Guterman

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

An auto-adaptive Neuro-Fuzzy segmentation and edge detection architecture is presented. The system consists of a multilayer perceptron (MLP) network that performs image segmentation by adaptive thresholding of the input image using labels automatically preselected by a fuzzy clustering technique. The proposed architecture is feedforward, but unlike the conventional MLP the learning is unsupervised. The output status of the network is described as a fuzzy set. Fuzzy entropy is used as a measure of the error of the segmentation system as well as a criterion for determining potential edge pixels.

Original languageEnglish
Pages1063-1068
Number of pages6
StatePublished - 1 Jan 1997
EventProceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3) - Barcelona, Spain
Duration: 1 Jul 19975 Jul 1997

Conference

ConferenceProceedings of the 1997 6th IEEE International Conference on Fussy Systems, FUZZ-IEEE'97. Part 1 (of 3)
CityBarcelona, Spain
Period1/07/975/07/97

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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