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dc.contributor.authorHansen, Pierreen
dc.contributor.authorLazić, Jasminaen
dc.contributor.authorMladenović, Nenaden
dc.date.accessioned2020-05-02T16:42:12Z-
dc.date.available2020-05-02T16:42:12Z-
dc.date.issued2007-01-01en
dc.identifier.issn1471-678Xen
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/2532-
dc.description.abstractColour image quantization is a data compression technique that reduces the total set of colours in a digital image to a representative subset. This problem is first expressed as a large M-median one. The advantages of this model over the usual minimum sum-of-squares model are discussed first and then, the heuristic based on variable neighbourhood search metaheuristic is applied to solve it. Computational experience proves that this approach compares favourably with two other recent state-of-the-art heuristics, based on genetic and particle swarm searches.en
dc.publisherOxford University Press-
dc.relation.ispartofIMA Journal of Management Mathematicsen
dc.subjectClustering problem | Colour image quantization | M-median problem | Sum-of-squares | Variable neighbourhood decomposition searchen
dc.titleVariable neighbourhood search for colour image quantizationen
dc.typeArticleen
dc.identifier.doi10.1093/imaman/dpm008en
dc.identifier.scopus2-s2.0-34147130184en
dc.relation.firstpage207en
dc.relation.lastpage221en
dc.relation.issue2en
dc.relation.volume18en
item.cerifentitytypePublications-
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.orcid0000-0001-6655-0409-
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