Color image segmentation by multilevel thresholding based on harmony search algorithm

Viktor Tuba, Marko Beko, Milan Tuba

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

One of the important problems and active research topics in digital image precessing is image segmentation where thresholding is a simple and effective technique for this task. Multilevel thresholding is computationally complex task so different metaheuristics have been used to solve it. In this paper we propose harmony search algorithm for finding optimal threshold values in color images by Otsu’s method. We tested our proposed algorithm on six standard benchmark images and compared the results with other approach from literature. Our proposed method outperformed other approach considering all performance metrics.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning – IDEAL 2017 - 18th International Conference, Proceedings
PublisherSpringer Verlag
Pages571-579
Number of pages9
ISBN (Print)9783319689340
DOIs
Publication statusPublished - 2017
Event18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017 - Guilin, China
Duration: 30 Oct 20171 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10585 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017
CountryChina
CityGuilin
Period30/10/171/11/17

Keywords

  • Color images
  • Harmony search algorithm
  • Image segmentation
  • Metaheuristic algorithms
  • Multilevel thresholding
  • Otsu’s method

Fingerprint Dive into the research topics of 'Color image segmentation by multilevel thresholding based on harmony search algorithm'. Together they form a unique fingerprint.

Cite this