Multilevel minimum cross entropy threshold selection based on quantum particle swarm optimization

Zhao Yong, Fang Zongde, Wang Kanwei, Pang Hui

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

23 Scopus citations

Abstract

The minimum cross entropy thresholding (MCET) has been proven as an efficient method in image segmentation for bilevel thresholding. However, this method is computationally intensive when extended to multilevel thresholding. This paper first employs a recursive programming technique which can reduce an order of magnitude for computing the MCET fitness function. Then, a quantum particle swarm optimization (QPSO) algorithm is proposed for searching the nearoptimal MCET thresholds. The experimental results show that the proposed QPSO-based algorithm can get ideal segmentation result with less computation cost.

Original languageEnglish
Title of host publicationProceedings - SNPD 2007
Subtitle of host publicationEighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Pages65-69
Number of pages5
DOIs
StatePublished - 2007
EventSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Qingdao, China
Duration: 30 Jul 20071 Aug 2007

Publication series

NameProceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Volume2

Conference

ConferenceSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Country/TerritoryChina
CityQingdao
Period30/07/071/08/07

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