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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier6qtX3pFwXQZeBBx/GLBoU
Repositorysid.inpe.br/banon/2005/07.15.21.19
Last Update2005:07.15.03.00.00 (UTC) administrator
Metadatasid.inpe.br/banon/2005/07.15.21.19.20
Metadata Last Update2020:02.19.03.19.22 (UTC) administrator
Citation KeyLopesCons:2005:RBPeMo
TitleA RBFN perceptive model for image thresholding
FormatOn-line
Year2005
Access Date2021, Nov. 27
Number of Files1
Size385 KiB
Context area
Author1 Lopes, Fabrício Martins
2 Consularo, Luís Augusto
Affiliation1 CEFET-PR - Centro Federal de Educação Tecnológica do Paraná
2 Av. Alberto Carazzai, 1640, 86300-000, Cornélio Procópio, PR, Brasil.
3 UNIMEP - Universidade Metodista de Piracicaba
4 Rodovia do Açúcar, Km 156, 13400-911, Piracicaba, SP, Brasil.
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
e-Mail Addressfabricio@cp.cefetpr.br
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2005-07-15 21:19:21 :: fabricio@cp.cefetpr.br -> banon ::
2005-07-18 14:25:29 :: banon -> fabricio@cp.cefetpr.br ::
2008-07-17 14:11:01 :: fabricio@cp.cefetpr.br -> banon ::
2008-08-26 15:17:03 :: banon -> administrator ::
2009-08-13 20:37:58 :: administrator -> banon ::
2010-08-28 20:01:20 :: banon -> administrator ::
2020-02-19 03:19:22 :: administrator -> :: 2005
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsSegmentation
Thresholding
RBFN
Psychophysical
AbstractThe digital image segmentation challenge has demanded the development of a plethora of methods and approaches. A quite simple approach, the thresholding, has still been intensively applied mainly for real-time vision applications. However, the threshold criteria often depend on entropic or statistical image features. This work searches a relationship between these features and subjective human threshold decisions. Then, an image thresholding model based on these subjective decisions and global statistical features was developed by training a Radial Basis Functions Network (RBFN). This work also compares the automatic thresholding methods to the human responses. Furthermore, the RBFN-modeled answers were compared to the automatic thresholding. The results show that entropic-based method was closer to RBFN-modeled thresholding than variance-based method. It was also found that another automatic method which combines global and local criteria presented higher correlation with human responses.
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data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/GLBoU
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/GLBoU
Languageen
Target Filelopesf_rbfnperceptive.pdf
User Groupfabricio@cp.cefetpr.br
administrator
Visibilityshown
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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 edition electronicmailaddress group holdercode isbn issn label lineage mark mirrorrepository 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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