Title

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

Authors
Publication Genève, 1998
Collection Technical report VISION; 98.04
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.
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Research group Computer Vision and Multimedia Laboratory
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. 1998 https://archive-ouverte.unige.ch/unige:48054

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