Oppositional fuzzy image thresholding

Fares S. Al-Qunaieer, Shahryar Rahnamayan, Hamid R. Tizhoosh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In many image processing applications, image thresholding is considered to be an important task. Opposition-Based Learning (OBL) was recently introduced and used to enhance different computation algorithms. In this paper, a new thresholding algorithm is proposed by utilizing the concept of opposite fuzzy sets. The algorithm is applied on general set of images and compared with the previous opposition-based thresholding algorithm [1] and a commonly used thresholding method, namely the Otsu method. The most reliable results on the test data are achieved using the proposed algorithm

Original languageEnglish (US)
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010
DOIs
StatePublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - Barcelona, Spain
Duration: Jul 18 2010Jul 23 2010

Publication series

Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010
Country/TerritorySpain
CityBarcelona
Period7/18/107/23/10

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

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