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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Repositorysid.inpe.br/sibgrapi@80/2007/09.21.12.42
Last Update2007:09.21.12.42.18 administrator
Metadatasid.inpe.br/sibgrapi@80/2007/09.21.12.42.19
Metadata Last Update2020:02.19.03.06.19 administrator
Citation KeyBastosConc:2007:AuTeSe
TitleAutomatic Texture Segmentation Based on k-means Clustering and Co-occurrence Features
FormatOn-line
Year2007
DateOct. 7-10, 2007
Access Date2021, Jan. 16
Number of Files1
Size90 KiB
Context area
Author1 Bastos, Lucas
2 Conci, Aura
Affiliation1 Universidade Federal Fluminense
2 Universidade Federal Fluminense
EditorGonçalves, Luiz
Wu, Shin Ting
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Tertiary TypeTechnical Poster
History2008-07-17 14:09:45 :: aconci@ic.uff.br -> administrator ::
2009-08-13 20:38:44 :: administrator -> banon ::
2010-08-28 20:02:32 :: banon -> administrator ::
2020-02-19 03:06:19 :: administrator -> :: 2007
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Is the master or a copy?is the master
Content Stagecompleted
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Content TypeExternal Contribution
KeywordsHaralick features,automatic texture segmentation, grey level co-occurrence.
AbstractThis work presents a method for automatic texture segmentation based on k-means clustering technique and cooccurrence texture features. A set of up to eight features were extracted from a 256 grey-level co-occurrence information. These features were used to segment image regions regarding the textural homogeneity of its areas. As the process of calculating co-occurrence information demands the majority of computational time required,we propose a new methodology based on a grey-level cooccurrence indexed list (GLCIL) for fast element access and highly optimize this step in the algorithm. Besides that, we compare the efficiency of the proposed method against the GLCM and GLCLL algorithms. The GLCIL shows to be the most efficient method in terms of computational time. Additionally, traditional Brodatz textures and others examples of the literature were tested to evaluate the appropriateness and robustness of the method.
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data URLhttp://urlib.net/rep/sid.inpe.br/sibgrapi@80/2007/09.21.12.42
zipped data URLhttp://urlib.net/zip/sid.inpe.br/sibgrapi@80/2007/09.21.12.42
Languageen
Target Filelucasfinal.pdf
User Groupaconci@ic.uff.br
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Mirror Repositorysid.inpe.br/sibgrapi@80/2007/08.02.16.22
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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