Neuro-fuzzy system for adaptive multilevel image segmentation

Victor Boskovitz, Hugo Guterman

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

An auto-adaptive Neuro-Fuzzy segmentation architecture is presented. The system consists of a multilayer perceptron (MLP) network that performs 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 system.

Original languageEnglish
Pages208-211
Number of pages4
StatePublished - 1 Dec 1996
EventProceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel - Jerusalem, Isr
Duration: 5 Nov 19966 Nov 1996

Conference

ConferenceProceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel
CityJerusalem, Isr
Period5/11/966/11/96

ASJC Scopus subject areas

  • Engineering (all)

Fingerprint

Dive into the research topics of 'Neuro-fuzzy system for adaptive multilevel image segmentation'. Together they form a unique fingerprint.

Cite this