dc.creatorFlorindo, João Batista
dc.creatorBruno, Odemir Martinez
dc.date.accessioned2016-09-20T12:46:43Z
dc.date.accessioned2018-07-04T17:08:25Z
dc.date.available2016-09-20T12:46:43Z
dc.date.available2018-07-04T17:08:25Z
dc.date.created2016-09-20T12:46:43Z
dc.date.issued2014-06
dc.identifierPattern Recognition Letters, Amsterdam : Elsevier BV, v. 42, p. 107-114, June 2014
dc.identifier0167-8655
dc.identifierhttp://www.producao.usp.br/handle/BDPI/50770
dc.identifier10.1016/j.patrec.2014.01.009
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1645190
dc.description.abstractIn this work, we propose a novel technique for obtaining descriptors of gray-level texture images. The descriptors are provided by applying a multiscale transform to the fractal dimension of the image estimated through the probability (Voss) method. The effectiveness of the descriptors is verified in a classification task using benchmark over texture datasets. The results obtained demonstrate the efficiency of the proposed method as a tool for the description and discrimination of texture images.
dc.languageeng
dc.publisherElsevier BV
dc.publisherAmsterdam
dc.relationPattern Recognition Letters
dc.rightsCopyright Elsevier B.V.
dc.rightsrestrictedAccess
dc.subjectPattern recognition
dc.subjectFractal dimension
dc.subjectFractal descriptors
dc.subjectProbability dimension
dc.subjectTexture analysis
dc.titleFractal descriptors based on the probability dimension: a texture analysis and classification approach
dc.typeArtículos de revistas


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