TY  - RPRT
ID  - SMM1998
T1  - content-based query of image databases, inspirations from text retrieval: inverted files, frequency-based weights and relevance feedback
A1  - Squire, David McG.
A1  - Müller, Wolfgang
A1  - Müller, Henning
A1  - Raki, Jilali
Y1  - 1998
IS  - 98.04
T2  - Computer Vision Group, Computing Centre, University of Geneva
AD  - rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve, Switzerland
N2  - 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.
M1  - vgproject={viper
M1  - cbir}
M1  - 
vgclass={report}
ER  -