Wavelet-Based Hierarchical Organization of Large Image Databases: ISAR and Face Recognition

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dc.contributor.authorBaras, John S.en_US
dc.contributor.authorWolk, S.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:05:37Z
dc.date.available2007-05-23T10:05:37Z
dc.date.issued1998en_US
dc.description.abstractWe present a method for constructing efficient hierarchical organization of image databases for fast recognition and classification. The method combines a wavelet preprocessor with a Tree-Structured-Vector-Quantization for clustering. We show results of application of the method to ISAR data from ships and to face recognition based on photograph databases. In the ISAR case we show how the method constructs a multi-resolution aspect graph for each target. <p><center><I>This paper was presented at the "SPIE's 12th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls (Aerosense'98)", April 13-17, 1998, Orlando, Florida.</I></center>en_US
dc.format.extent351273 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5942
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1998-11en_US
dc.subjectwaveletsen_US
dc.subjecthierarchical classificationen_US
dc.subjectaspect graphen_US
dc.subjectface identificationen_US
dc.titleWavelet-Based Hierarchical Organization of Large Image Databases: ISAR and Face Recognitionen_US
dc.typeTechnical Reporten_US

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