dc.creatorBackes, Andre Ricardo
dc.creatorCasanova, Dalcimar
dc.creatorBruno, Odemir Martinez
dc.date.accessioned2013-08-14T17:56:38Z
dc.date.accessioned2018-07-04T15:54:44Z
dc.date.available2013-08-14T17:56:38Z
dc.date.available2018-07-04T15:54:44Z
dc.date.created2013-08-14T17:56:38Z
dc.date.issued2012
dc.identifierPATTERN RECOGNITION, OXFORD, v. 45, n. 5, supl. 1, Part 1, pp. 1984-1992, MAY, 2012
dc.identifier0031-3203
dc.identifierhttp://www.producao.usp.br/handle/BDPI/32552
dc.identifier10.1016/j.patcog.2011.11.009
dc.identifierhttp://dx.doi.org/10.1016/j.patcog.2011.11.009
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1629099
dc.description.abstractColor texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. (C) 2011 Elsevier Ltd. All rights reserved.
dc.languageeng
dc.publisherELSEVIER SCI LTD
dc.publisherOXFORD
dc.relationPATTERN RECOGNITION
dc.rightsCopyright ELSEVIER SCI LTD
dc.rightsopenAccess
dc.subjectCOLOR TEXTURE ANALYSIS
dc.subjectFRACTAL DIMENSION
dc.subjectCOMPLEXITY
dc.subjectFEATURE EXTRACTION
dc.subjectCLASSIFICATION
dc.titleColor texture analysis based on fractal descriptors
dc.typeArtículos de revistas


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