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Reference TypeConference Proceedings
Sitesibgrapi.sid.inpe.br
Identifier6qtX3pFwXQZeBBx/GLwLx
Repositorysid.inpe.br/banon/2005/07.15.17.44
Last Update2005:07.15.03.00.00 administrator
Metadatasid.inpe.br/banon/2005/07.15.17.45.01
Metadata Last Update2020:02.19.03.19.19 administrator
Citation KeyConsularoCesa:2005:QuInGr
TitleQuadtree-based inexact graph matching for image analysis
FormatOn-line
Year2005
Date9-12 Oct. 2005
Access Date2020, Dec. 04
Number of Files1
Size208 KiB
Context area
Author1 Consularo, Luís Augusto
2 Cesar Jr, Roberto Marcondes
Affiliation1 UNIMEP - Methodist University of Piracicaba
2 IME-USP - Department of Computer Science - IME - University of São Paulo
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
e-Mail Addresslaconsul@unimep.br
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2005-07-15 21:42:07 :: consularo -> banon ::
2005-07-18 14:24:29 :: banon -> consularo ::
2008-07-17 14:11:01 :: consularo -> banon ::
2008-08-26 15:17:03 :: banon -> administrator ::
2009-08-13 20:37:54 :: administrator -> banon ::
2010-08-28 20:01:19 :: banon -> administrator ::
2020-02-19 03:19:19 :: administrator -> :: 2005
Content and structure area
Is the master or a copy?is the master
Document Stagecompleted
Transferable1
Content TypeExternal Contribution
Tertiary TypeFull Paper
Keywordsinexact graph matching, quadtree, homomorphism.
AbstractThis paper presents a new method for segmentation and recognition of image objects based on structural pattern recognition. The input image is decomposed into regions through a quadtree algorithm. The decomposed image is represented by an attributed relational graph (ARG) named input graph. The objects to be recognized are also stored in an ARG named model graph. Object segmentation and recognition are accomplished by matching the input graph to the model graph. The possible inexact matches between the two graphs are cliques of the association graph between them. An objective function, to be optimized, is defined for each clique in order to measure how suitable is the match between the graphs. Therefore, recognition is modeled as an optimization procedure. A beam-search algorithm is used to optimize the objective function. Experimental results corroborating the proposed approach are presented.
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Languageen
Target Fileconsularol_quadtree.pdf
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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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