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Content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback

Presented at Kangerlussuaq (Greenland), Jun 7-11
Publication date1999
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 $\mathcal{O}(104)$ 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.

Citation (ISO format)
SQUIRE, David et al. Content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback. In: The 11th Scandinavian Conference on Image Analysis. Kangerlussuaq (Greenland). [s.l.] : [s.n.], 1999. p. 143–149.
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