dc.creatorBackes, André Ricardo
dc.creatorCasanova, Dalcimar
dc.creatorBruno, Odemir Martinez
dc.date.accessioned2014-05-26T18:20:50Z
dc.date.accessioned2018-07-04T16:46:43Z
dc.date.available2014-05-26T18:20:50Z
dc.date.available2018-07-04T16:46:43Z
dc.date.created2014-05-26T18:20:50Z
dc.date.issued2013-01
dc.identifierInformation Sciences, Philadelphia : Elsevier, v. 219, p. 168-180, Jan. 2013
dc.identifier0020-0255
dc.identifierhttp://www.producao.usp.br/handle/BDPI/45037
dc.identifier10.1016/j.ins.2012.07.003
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1640238
dc.description.abstractIn this paper, we propose a novel texture analysis method using the complex network theory. We investigated how a texture image can be effectively represented, characterized and analyzed in terms of a complex network. The proposed approach uses degree measurements to compose a set of texture descriptors. The results show that the method is very robust, and it presents a excellent texture discrimination for all considered classes, overcoming traditional texture methods.
dc.languageeng
dc.publisherElsevier
dc.publisherPhiladelphia
dc.relationInformation Sciences
dc.rightsCopyright Elsevier Inc.
dc.rightsrestrictedAccess
dc.subjectTexture analysis
dc.subjectTexture recognition
dc.subjectComplex network
dc.titleTexture analysis and classification: a complex network-based approach
dc.typeArtículos de revistas


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