Fuzziness measure approach to automatic histogram threshold

Detalhes bibliográficos
Autor(a) principal: Lopes, Nuno Vieira
Data de Publicação: 2007
Outros Autores: Bustince, Humberto, Filipe, Vitor, Melo-Pinto, Pedro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.8/3551
Resumo: In 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.
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spelling Fuzziness measure approach to automatic histogram thresholdIn 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.CRC PressIC-OnlineLopes, Nuno VieiraBustince, HumbertoFilipe, VitorMelo-Pinto, Pedro2018-09-26T08:30:56Z2007-082007-08-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.8/3551eng9780415457774metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-17T15:47:25Zoai:iconline.ipleiria.pt:10400.8/3551Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:47:37.677964Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Fuzziness measure approach to automatic histogram threshold
title Fuzziness measure approach to automatic histogram threshold
spellingShingle Fuzziness measure approach to automatic histogram threshold
Lopes, Nuno Vieira
title_short Fuzziness measure approach to automatic histogram threshold
title_full Fuzziness measure approach to automatic histogram threshold
title_fullStr Fuzziness measure approach to automatic histogram threshold
title_full_unstemmed Fuzziness measure approach to automatic histogram threshold
title_sort Fuzziness measure approach to automatic histogram threshold
author Lopes, Nuno Vieira
author_facet Lopes, Nuno Vieira
Bustince, Humberto
Filipe, Vitor
Melo-Pinto, Pedro
author_role author
author2 Bustince, Humberto
Filipe, Vitor
Melo-Pinto, Pedro
author2_role author
author
author
dc.contributor.none.fl_str_mv IC-Online
dc.contributor.author.fl_str_mv Lopes, Nuno Vieira
Bustince, Humberto
Filipe, Vitor
Melo-Pinto, Pedro
description In 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.
publishDate 2007
dc.date.none.fl_str_mv 2007-08
2007-08-01T00:00:00Z
2018-09-26T08:30:56Z
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dc.publisher.none.fl_str_mv CRC Press
publisher.none.fl_str_mv CRC Press
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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