dc.creatorBRUNO, Odemir Martinez
dc.creatorNONATO, Luis Gustavo
dc.creatorPAZOTI, Mario Augusto
dc.creatorBATISTA NETO, Joao
dc.date.accessioned2012-10-20T03:31:01Z
dc.date.accessioned2018-07-04T15:38:02Z
dc.date.available2012-10-20T03:31:01Z
dc.date.available2018-07-04T15:38:02Z
dc.date.created2012-10-20T03:31:01Z
dc.date.issued2008
dc.identifierPATTERN RECOGNITION LETTERS, v.29, n.11, p.1675-1683, 2008
dc.identifier0167-8655
dc.identifierhttp://producao.usp.br/handle/BDPI/28790
dc.identifier10.1016/j.patrec.2008.04.017
dc.identifierhttp://dx.doi.org/10.1016/j.patrec.2008.04.017
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1625432
dc.description.abstractSuccessful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,
dc.languageeng
dc.publisherELSEVIER SCIENCE BV
dc.relationPattern Recognition Letters
dc.rightsCopyright ELSEVIER SCIENCE BV
dc.rightsrestrictedAccess
dc.subjectimage analysis
dc.subjectimage retrieval
dc.subjecttopological control
dc.subjectpattern recognition
dc.titleTopological multi-contour decomposition for image analysis and image retrieval
dc.typeArtículos de revistas


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