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dc.contributor.authorAkçay, H. Gokhanen_US
dc.contributor.authorAksoy, Selimen_US
dc.coverage.spatialAntalya, Turkeyen_US
dc.date.accessioned2016-02-08T12:19:23Z
dc.date.available2016-02-08T12:19:23Z
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/11693/28392
dc.descriptionDate of Conference: 20-22 April 2011en_US
dc.description.abstractWe present an unsupervised hierarchical segmentation algorithm for detecting complex heterogeneous image structures that are comprised of simpler homogeneous primitive objects. The first step segments primitive objects with uniform spectral content. Then, the co-occurrence information between neighboring regions is modeled and clustered. We assume that dense clusters of this co-occurrence space can be considered significant. Finally, the neighboring regions within these clusters are merged to obtain the next level in the segmentation hierarchy. The experiments show that the algorithm that iteratively clusters and merges region groups is able to segment heterogeneous structures in a hierarchical manner. © 2011 IEEE.en_US
dc.language.isoTurkishen_US
dc.source.title2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2011.5929821en_US
dc.subjectCo-occurrenceen_US
dc.subjectDense clustersen_US
dc.subjectHeterogeneous structuresen_US
dc.subjectHierarchical segmentationen_US
dc.subjectImage Structuresen_US
dc.subjectSpectral contenten_US
dc.subjectAlgorithmsen_US
dc.subjectSignal detectionen_US
dc.subjectImage segmentationen_US
dc.titleDetection of heterogeneous structures using hierarchical segmentationen_US
dc.title.alternativeSiradüzensel bölütleme ile türdeş olmayan yapilarin sezimien_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineering
dc.citation.spage996en_US
dc.citation.epage999en_US
dc.identifier.doi10.1109/SIU.2011.5929821en_US
dc.publisherIEEEen_US


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