Hierarchical segmentation of complex structures

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dc.citation.epage1123en_US
dc.citation.spage1120en_US
dc.contributor.authorAkçay, H. Gökhanen_US
dc.contributor.authorAksoy, Selimen_US
dc.contributor.authorSoille P.en_US
dc.coverage.spatialIstanbul, Turkeyen_US
dc.date.accessioned2016-02-08T12:22:40Z
dc.date.available2016-02-08T12:22:40Z
dc.date.issued2010en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 23-26 Aug. 2010en_US
dc.description.abstractWe present an unsupervised hierarchical segmentation algorithm for detection of complex heterogeneous image structures that are comprised of simpler homogeneous primitive objects. An initial segmentation step produces regions corresponding to primitive objects with uniform spectral content. Next, the transitions between neighboring regions are modeled and clustered. We assume that the clusters that are dense and large enough in this transition space can be considered as significant. Then, the neighboring regions belonging to the significant clusters are merged to obtain the next level in the hierarchy. The experiments show that the algorithm that iteratively clusters and merges region groups is able to segment high-level complex structures in a hierarchical manner. © 2010 IEEE.en_US
dc.identifier.doi10.1109/ICPR.2010.280en_US
dc.identifier.issn1051-4651
dc.identifier.urihttp://hdl.handle.net/11693/28515
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICPR.2010.280en_US
dc.source.title2010 20th International Conference on Pattern Recognitionen_US
dc.subjectComplex structureen_US
dc.subjectHierarchical segmentationen_US
dc.subjectImage Structuresen_US
dc.subjectInitial segmentationen_US
dc.subjectSpectral contenten_US
dc.subjectPattern recognitionen_US
dc.subjectImage segmentationen_US
dc.titleHierarchical segmentation of complex structuresen_US
dc.typeConference Paperen_US

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