Modeling of remote sensing image content using attributed relational graphs

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dc.citation.epage483en_US
dc.citation.spage475en_US
dc.contributor.authorAksoy, Selimen_US
dc.coverage.spatialHong Kong, China
dc.date.accessioned2016-02-08T11:48:49Z
dc.date.available2016-02-08T11:48:49Z
dc.date.issued2006-08en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 17-19 August, 2006
dc.descriptionConference name: Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR), 2006
dc.description.abstractAutomatic content modeling and retrieval in remote sensing image databases are important and challenging problems. Statistical pattern recognition and computer vision algorithms concentrate on feature-based analysis and representations in pixel or region levels whereas syntactic and structural techniques focus on modeling symbolic representations for interpreting scenes. We describe a hybrid hierarchical approach for image content modeling and retrieval. First, scenes are decomposed into regions using pixel-based classifiers and an iterative split-and-merge algorithm. Next, spatial relationships of regions are computed using boundary, distance and orientation information based on different region representations. Finally, scenes are modeled using attributed relational graphs that combine region class information and spatial arrangements. We demonstrate the effectiveness of this approach in query scenarios that cannot be expressed by traditional approaches but where the proposed models can capture both feature and spatial characteristics of scenes and can retrieve similar areas according to their high-level semantic content. © Springer-Verlag Berlin Heidelberg 2006.en_US
dc.identifier.doi10.1007/11815921_52en_US
dc.identifier.urihttp://hdl.handle.net/11693/27257
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttps://doi.org/10.1007/11815921_52en_US
dc.source.titleJoint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR), 2006en_US
dc.subjectComputer simulationen_US
dc.subjectDatabase systemsen_US
dc.subjectGraph theoryen_US
dc.subjectPattern recognitionen_US
dc.subjectRemote sensingen_US
dc.subjectAutomatic content modelingen_US
dc.subjectRemote sensing imagesen_US
dc.subjectSemantic contenten_US
dc.subjectSplit-and-merge algorithmsen_US
dc.subjectContent based retrievalen_US
dc.titleModeling of remote sensing image content using attributed relational graphsen_US
dc.typeConference Paperen_US

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