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Content-based query of image databases: inspirations from text retrieval

Published in Pattern Recognition Letters. 2000, vol. 21, no. 13-14, p. 1193-1198
Abstract This paper reports the application of techniques inspired by text retrieval research to content-based image retrieval. In particular, we show how the use of an inverted file data structure permits the use of an extremely high-dimensional feature-space, 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 weighting scheme based on feature frequencies is used to combine disparate 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.
Keywords Content-based image retrievalInverted filesRelevance feedback
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Research groups Computer Vision and Multimedia Laboratory
Multimodal Interaction Group
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SQUIRE, David et al. Content-based query of image databases: inspirations from text retrieval. In: Pattern Recognition Letters, 2000, vol. 21, n° 13-14, p. 1193-1198. doi: 10.1016/S0167-8655(00)00081-7 https://archive-ouverte.unige.ch/unige:47502

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Deposited on : 2015-03-03

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