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Technical Reports


  • David McG. Squire, Wolfgang Müller, Henning Müller and Jilali Raki, Content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback. Tech. Rep. 98.04, Computer Vision Group, Computing Centre, University of Geneva, rue Général Dufour, 24, CH-1211 Genève, Switzerland, November 1998.

    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 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.