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content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback
Type of publication: Inproceedings
Citation: SMM1999
Booktitle: Scandinavian Conference on Image Analysis
Year: 1999
Pages: 143-149
Crossref: SCIA'99
Abstract: In this paper we report the application of techniques inspired by text retrieval research to the content-based query of image databases. In particular, we show how the use of an inverted file data structure permits the use of a feature space of $\mathcal{O}(10^4)$ dimensions, by restricting search to the subspace spanned by the features present in the query. A suitably sparse set of colour and texture features is proposed. A scheme based on the frequency of occurrence of features in both individual images and in the whole collection provides a means of weighting possibly incommensurate features in a compatible manner, and naturally extends to incorporate relevance feedback queries. The use of relevance feedback is shown consistently to improve system performance, as measured by precision and recall.
Userfields: vgproject={cbir,viper}, vgclass={refpap},
Keywords: Content-based image retrieval, image retrieval, inverted file, text retrieval
Authors Squire, David McG.
Müller, Wolfgang
Müller, Henning
Raki, Jilali
Added by: []
Total mark: 0
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  • SMM1999.pdf
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