English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/30413
Share/Impact:
Statistics
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

DC FieldValueLanguage
dc.contributor.authorSerratosa, Francesc-
dc.contributor.authorSanfeliu, Alberto-
dc.date.accessioned2010-12-17T08:06:13Z-
dc.date.available2010-12-17T08:06:13Z-
dc.date.issued2005-
dc.identifier.citation2nd Iberian Conference on Pattern Recognition and Image Analysis: pp. 131-138 (2005)-
dc.identifier.isbn9783540261544-
dc.identifier.urihttp://hdl.handle.net/10261/30413-
dc.descriptionIberian Conference on Pattern Recognition and Image Analysis (IbPRIA), 2005, Estoril (Portugal)-
dc.description.abstractA branch-and-bound algorithm for matching Attributed Graphs (AGs) with Second-Order Random Graphs (SORGs) is presented. We show that the search space explored by this algorithm is drastically reduced by using the information of the 2nd-order joint probabilities of vertices of the SORGs. A SORG is a model graph, described elsewhere, that contains 1st and 2nd-order order probabilities of attribute relations between elements for representing a set of AGs compactly. In this work, we have applied SORGs and the reported algorithm to the recognition of real-life objects on images and the results show that the use of 2nd-order relations between vertices is not only useful to decrease the run time but also to increase the correct classification ratio.-
dc.language.isoeng-
dc.publisherSpringer-
dc.rightsopenAccess-
dc.subjectPattern recognition-
dc.subjectPattern recognition systems-
dc.titleMatching attributed graphs: 2nd-order probabilities for pruning the search tree-
dc.typecomunicación de congreso-
dc.identifier.doihttp://dx.doi.org/10.1007/b136831-
dc.description.peerreviewedPeer Reviewed-
Appears in Collections:(IRII) Comunicaciones congresos
Files in This Item:
File Description SizeFormat 
doc1.pdf321,39 kBAdobe PDFThumbnail
View/Open
Show simple item record
 


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.