Comparative study of global color and texture descriptors for web image retrieval

dc.creatorPenatti, OAB
dc.creatorValle, E
dc.creatorTorres, RD
dc.date2012
dc.dateFEB
dc.date2014-07-30T14:00:01Z
dc.date2015-11-26T16:32:42Z
dc.date2014-07-30T14:00:01Z
dc.date2015-11-26T16:32:42Z
dc.date.accessioned2018-03-28T23:14:12Z
dc.date.available2018-03-28T23:14:12Z
dc.identifierJournal Of Visual Communication And Image Representation. Academic Press Inc Elsevier Science, v. 23, n. 2, n. 359, n. 380, 2012.
dc.identifier1047-3203
dc.identifierWOS:000300198900013
dc.identifier10.1016/j.jvcir.2011.11.002
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/56154
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/56154
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1270603
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionThis paper presents a comparative study of color and texture descriptors considering the Web as the environment of use. We take into account the diversity and large-scale aspects of the Web considering a large number of descriptors (24 color and 28 texture descriptors, including both traditional and recently proposed ones). The evaluation is made on two levels: a theoretical analysis in terms of algorithms complexities and an experimental comparison considering efficiency and effectiveness aspects. The experimental comparison contrasts the performances of the descriptors in small-scale datasets and in a large heterogeneous database containing more than 230 thousand images. Although there is a significant correlation between descriptors performances in the two settings, there are notable deviations, which must be taken into account when selecting the descriptors for large-scale tasks. An analysis of the correlation is provided for the best descriptors, which hints at the best opportunities of their use in combination. (C) 2011 Elsevier Inc. All rights reserved.
dc.description23
dc.description2
dc.description359
dc.description380
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionMicrosoft Research
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFAPESP [2006/59525-1, 2007/52015-0, 2009/10554-8, 2009/18438-7, 2009/05951-8]
dc.languageen
dc.publisherAcademic Press Inc Elsevier Science
dc.publisherSan Diego
dc.publisherEUA
dc.relationJournal Of Visual Communication And Image Representation
dc.relationJ. Vis. Commun. Image Represent.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectComparative study
dc.subjectColor descriptors
dc.subjectTexture descriptors
dc.subjectWeb
dc.subjectContent-based image retrieval
dc.subjectEfficiency and effectiveness
dc.subjectAsymptotic complexity
dc.subjectCorrelation analysis
dc.subjectRotation-invariant
dc.subjectFeatures
dc.subjectMpeg-7
dc.subjectClassification
dc.subjectScale
dc.subjectRepresentation
dc.subjectSegmentation
dc.subjectCorrelograms
dc.subjectRecognition
dc.subjectHistograms
dc.titleComparative study of global color and texture descriptors for web image retrieval
dc.typeArtículos de revistas


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