Image retrieval based on semantic contents involves extraction, modelling and indexing of content information. While extraction of abstract contents is a hard problem, it is only part of the bigger picture. In this paper we use knowledge about the semantic contents of images to improve retrieval effectiveness. In particular we use WordNet, an electronic lexical system for query and database expansion. Our content model facilitates novel uses of WordNet. We also propose a new normalization formula, an object significance scheme and evaluate their effectiveness with real user experiments. We describe the experiment setup and provide quantitative evaluation of each technique. Copyright 1997 ACM.