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Fuzziness measure approach to automatic histogram threshold

dc.contributor.authorLopes, Nuno Vieira
dc.contributor.authorBustince, Humberto
dc.contributor.authorFilipe, Vitor
dc.contributor.authorMelo-Pinto, Pedro
dc.date.accessioned2018-09-26T08:30:56Z
dc.date.available2018-09-26T08:30:56Z
dc.date.issued2007-08
dc.description.abstractIn this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems to find a minima of a criterion function are avoided. Similarity between gray levels is the key to find an optimal threshold. Two initial regions of gray levels, located at the boundaries of the histogram, are defined. Then, using an index of fuzziness, a similarity process is started to find the threshold point. A significant contrast between objects and background is assumed. Previous histogram equalization is used in small contrast images. No prior knowledge of the image is required.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.isbn9780415457774
dc.identifier.urihttp://hdl.handle.net/10400.8/3551
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherCRC Presspt_PT
dc.titleFuzziness measure approach to automatic histogram thresholdpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlacePortopt_PT
oaire.citation.endPage299pt_PT
oaire.citation.startPage295pt_PT
oaire.citation.titleProceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processingpt_PT
person.familyNameVieira Lopes
person.givenNameNuno
person.identifier.ciencia-idE117-67AC-0B45
person.identifier.orcid0000-0002-2232-1839
person.identifier.scopus-author-id26031536700
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication0d39fc9c-397b-4d8a-857a-3d4da42277a6
relation.isAuthorOfPublication.latestForDiscovery0d39fc9c-397b-4d8a-857a-3d4da42277a6

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