Scene classification for content-based image retrieval
2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIU
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Please cite this item using this persistent URLhttp://hdl.handle.net/11693/26845
Content-based image indexing and retrieval have become important research problems with the use of large databases in a wide range of areas. In this study, a content-based image retrieval system that is based on scene classification for image indexing is proposed. Instead of using low-level features directly, semantic class information that is obtained as a result of scene classification is used during indexing. The traditional "bag of words" approach is modified for classifying the scenes. In order to minimize the semantic gap, a relevance feedback approach that is based on one-class classification is also integrated. The support vector data description is used for learning during feedback iterations. The experiments using the Corel data set show good results for both classification and retrieval. ©2008 IEEE.
KeywordsBag of words
Content-based image retrieval systems
Content-based image retrievals
Image indexing and retrievals
Support vector data descriptions
Content based retrieval
Indexing (of information)
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