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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/49L4DLS
Repositorysid.inpe.br/sibgrapi/2023/08.15.20.46
Last Update2023:08.15.22.21.55 (UTC) pmiranda@ime.usp.br
Metadata Repositorysid.inpe.br/sibgrapi/2023/08.15.20.46.46
Metadata Last Update2024:02.17.04.05.17 (UTC) administrator
DOI10.1109/SIBGRAPI59091.2023.10347172
Citation KeyKleineSantCappMira:2023:UnImSe
TitleUnsupervised Image Segmentation by Oriented Image Foresting Transform in Layered Graphs
FormatOn-line
Year2023
Access Date2024, Apr. 27
Number of Files1
Size1160 KiB
2. Context
Author1 Kleine, Felipe A. S.
2 Santos, Luiz F. D.
3 Cappabianco, Fábio A. M.
4 Miranda, Paulo A. V.
Affiliation1 IPT - Institute for Technological Research of the State of São Paulo, Brazil
2 University of São Paulo, Institute of Mathematics and Statistics, São Paulo, SP, Brazil
3 Instituto de Ciência e Tecnologia, São José dos Campos, SP, Brazil
4 University of São Paulo, Institute of Mathematics and Statistics, São Paulo, SP, Brazil
EditorClua, Esteban Walter Gonzalez
Körting, Thales Sehn
Paulovich, Fernando Vieira
Feris, Rogerio
e-Mail Addresspmiranda@ime.usp.br
Conference NameConference on Graphics, Patterns and Images, 36 (SIBGRAPI)
Conference LocationRio Grande, RS
DateNov. 06-09, 2023
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2023-08-15 22:21:55 :: pmiranda@ime.usp.br -> administrator :: 2023
2024-02-17 04:05:17 :: administrator -> pmiranda@ime.usp.br :: 2023
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsunsupervised image segmentation
image foresting transform
nested objects
AbstractIn this work, we address the problem of unsupervised image segmentation, subject to high-level constraints expected for the objects of interest. More specifically, we handle the segmentation of a hierarchy of objects with nested boundaries, each with its own expected boundary polarity constraint. To this end, this work successfully extends Hierarchical Layered Oriented Image Foresting Transform (HLOIFT), with the inclusion of nested object relations, to the unsupervised segmentation paradigm. On the other hand, this work can also be seen as an extension of Unsupervised OIFT (UOIFT) to include structural relationships of nested objects. The method is demonstrated in the segmentation of three datasets of colored images with superior performance compared to other existing techniques in graphs, requiring a smaller number of connected partitions to isolate the objects of interest in the images.
doc Directory Contentaccess
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/49L4DLS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/49L4DLS
Languageen
Target FileKleine-103.pdf
User Grouppmiranda@ime.usp.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
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 holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
7. Description control
e-Mail (login)pmiranda@ime.usp.br
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