dc.creatorBARBIERI, Andre L.
dc.creatorARRUDA, G. F. de
dc.creatorRODRIGUES, Francisco A.
dc.creatorBRUNO, Odemir M.
dc.creatorCOSTA, Luciano da Fontoura
dc.date.accessioned2012-10-20T04:17:17Z
dc.date.accessioned2018-07-04T15:42:39Z
dc.date.available2012-10-20T04:17:17Z
dc.date.available2018-07-04T15:42:39Z
dc.date.created2012-10-20T04:17:17Z
dc.date.issued2011
dc.identifierPHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v.390, n.3, p.512-518, 2011
dc.identifier0378-4371
dc.identifierhttp://producao.usp.br/handle/BDPI/29829
dc.identifier10.1016/j.physa.2010.10.015
dc.identifierhttp://dx.doi.org/10.1016/j.physa.2010.10.015
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1626469
dc.description.abstractAn entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.
dc.languageeng
dc.publisherELSEVIER SCIENCE BV
dc.relationPhysica A-statistical Mechanics and Its Applications
dc.rightsCopyright ELSEVIER SCIENCE BV
dc.rightsrestrictedAccess
dc.subjectEntropy
dc.subjectInformation theory
dc.subjectPattern recognition
dc.subjectImage analysis
dc.titleAn entropy-based approach to automatic image segmentation of satellite images
dc.typeArtículos de revistas


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