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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/GLBoU
Repositorysid.inpe.br/banon/2005/07.15.21.19
Last Update2005:07.15.03.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2005/07.15.21.19.20
Metadata Last Update2022:06.14.00.13.06 (UTC) administrator
DOI10.1109/SIBGRAPI.2005.8
Citation KeyLopesCons:2005:RBPeMo
TitleA RBFN perceptive model for image thresholding
FormatOn-line
Year2005
Access Date2024, Apr. 27
Number of Files1
Size385 KiB
2. Context
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, RN, Brazil
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 ::
2022-06-14 00:13:06 :: administrator -> :: 2005
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
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.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2005 > A RBFN perceptive...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > A RBFN perceptive...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
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
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46R3ED5
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.05.04.08 9
sid.inpe.br/banon/2001/03.30.15.38.24 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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