DSpace
 

EPrints@IIT Delhi >
Faculty Research Publicatons  >
Mathematics >

Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/944

Full metadata record

DC FieldValueLanguage
dc.contributor.authorKrishnapuram, Raghu-
dc.date.accessioned2005-10-18T05:49:07Z-
dc.date.available2005-10-18T05:49:07Z-
dc.date.issued2001-
dc.identifier.citationComputer Vision and Image Understanding, 83(3), 216–235en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/944-
dc.description.abstractIn this paper, we present a robust mixture decomposition technique that automatically finds a compact representation of the data in terms of components. We apply it to the problem of organizing databases for efficient retrieval. The time taken for retrieval is an order of magnitude smaller than that of exhaustive search methods.We also compare our approach with other methods for decomposition that use traditional criteria such as Akaike, Schwarz, and minimum description length.We report results on the VisTex texture image database from the MIT Media Lab.en
dc.format.extent987049 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectcategorizationen
dc.subjectimage databasesen
dc.subjectmixture decompositionen
dc.subjectrobust organizationen
dc.titleCategorization of image databases for efficient retrieval using robust mixture decompositionen
dc.typeArticleen
Appears in Collections:Mathematics

Files in This Item:

File Description SizeFormat
krishnapuramcat2001.pdf963.92 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback