Texture analysis and classification using deterministic tourist walk

dc.creatorBACKES, Andre Ricardo
dc.creatorGONCALVES, Wesley Nunes
dc.creatorMARTINEZ, Alexandre Souto
dc.creatorBRUNO, Odemir Martinez
dc.date.accessioned2012-10-20T04:15:08Z
dc.date.accessioned2018-07-04T15:41:45Z
dc.date.available2012-10-20T04:15:08Z
dc.date.available2018-07-04T15:41:45Z
dc.date.created2012-10-20T04:15:08Z
dc.date.issued2010
dc.identifierPATTERN RECOGNITION, v.43, n.3, p.685-694, 2010
dc.identifier0031-3203
dc.identifierhttp://producao.usp.br/handle/BDPI/29619
dc.identifier10.1016/j.patcog.2009.07.017
dc.identifierhttp://dx.doi.org/10.1016/j.patcog.2009.07.017
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1626259
dc.description.abstractIn this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.
dc.languageeng
dc.publisherELSEVIER SCI LTD
dc.relationPattern Recognition
dc.rightsCopyright ELSEVIER SCI LTD
dc.rightsrestrictedAccess
dc.subjectTexture analysis
dc.subjectTexture recognition
dc.subjectDeterministic walk
dc.subjectComplex systems
dc.titleTexture analysis and classification using deterministic tourist walk
dc.typeArtículos de revistas


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