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dc.contributor.authorAkçay H.G.en_US
dc.contributor.authorAksoy, S.en_US
dc.date.accessioned2016-02-08T12:13:47Z
dc.date.available2016-02-08T12:13:47Z
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/11693/28194
dc.description.abstractWe describe a new method for detecting compound structures in images by combining the statistical and structural characteristics of simple primitive objects. A graph is constructed by assigning the primitive objects to its vertices, and connecting potentially related objects using edges. Statistical information that is modeled using spectral, shape, and position data of individual objects as well as the structural information that is modeled in terms of spatial alignments of neighboring object groups are also encoded in this graph. Experiments using WorldView-2 data show that hierarchical clustering of the graph vertices can discover high-level compound structures that cannot be obtained using traditional techniques. © 2012 IEEE.en_US
dc.language.isoTurkishen_US
dc.source.title2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedingsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2012.6204794en_US
dc.subjectCompound structuresen_US
dc.subjectGraph vertexen_US
dc.subjectHier-archical clusteringen_US
dc.subjectIndividual objectsen_US
dc.subjectObject groupsen_US
dc.subjectPosition dataen_US
dc.subjectSpatial alignmenten_US
dc.subjectStatistical informationen_US
dc.subjectStructural characteristicsen_US
dc.subjectStructural featureen_US
dc.subjectStructural informationen_US
dc.subjectTraditional techniquesen_US
dc.subjectSignal processingen_US
dc.subjectGraph theoryen_US
dc.titleDetection of compound structures using clustering of statistical and structural featuresen_US
dc.title.alternativeİstatistiksel ve yapisal özniteliklerin öbeklenmesi ile bileşik yapilarin sezimien_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineering
dc.identifier.doi10.1109/SIU.2012.6204794en_US


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