Close
Metadata

Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier6qtX3pFwXQZG2LgkFdY/LM9QC
Repositorysid.inpe.br/sibgrapi@80/2006/07.17.01.11
Last Update2006:07.17.01.16.40 administrator
Metadatasid.inpe.br/sibgrapi@80/2006/07.17.01.11.20
Metadata Last Update2020:02.19.03.17.38 administrator
Citation KeyAudigierLotu:2006:DuThWa
TitleDuality between the watershed by image foresting transform and the fuzzy connectedness segmentation approaches
FormatOn-line
Year2006
Access Date2021, Jan. 27
Number of Files1
Size154 KiB
Context area
Author1 Audigier, Romaric
2 Lotufo, Roberto
Affiliation1 FEEC - Unicamp
2 FEEC - Unicamp
EditorOliveira Neto, Manuel Menezes de
Carceroni, Rodrigo Lima
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)
Conference LocationManaus
Date8-11 Oct. 2006
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2006-07-17 01:16:40 :: audigier -> banon ::
2006-08-30 21:46:31 :: banon -> audigier ::
2008-07-17 14:11:03 :: audigier -> administrator ::
2009-08-13 20:38:06 :: administrator -> banon ::
2010-08-28 20:02:23 :: banon -> administrator ::
2020-02-19 03:17:38 :: administrator -> :: 2006
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsimage segmentation, watershed, mathematical morphology, image foresting transform, graph theory, fuzzy connectedness.
AbstractThis paper makes a rereading of two successful image segmentation approaches, the fuzzy connectedness (FC) and the watershed (WS) approaches, by analyzing both by means of the Image Foresting Transform (IFT). This graph-based transform provides a sound framework for analyzing and implementing these methods. This paradigm allows to show the duality existing between the WS by IFT and the FC segmentation approaches. Both can be modeled by an optimal forest computation in a dual form (maximization of the similarities or minimization of the dissimilarities), the main difference being the input parameters: the weights associated to each arc of the graph representing the image. In the WS approach, such weights are based on the (possibly filtered) image gradient values whereas they are based on much more complex affinity values in the FC theory. An efficient algorithm for both FC and IFT-WS computation is proposed. Segmentation robustness issue is also discussed.
source Directory Contentthere are no files
agreement Directory Contentthere are no files
Conditions of access and use area
data URLhttp://urlib.net/rep/6qtX3pFwXQZG2LgkFdY/LM9QC
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/LM9QC
Languageen
Target Fileaudigier-dualityIFT.pdf
User Groupaudigier
administrator
Visibilityshown
Allied materials area
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
Notes area
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress 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

Close