The growing need for "intelligent" image retrieval systems to cope with the fast development of the digital imaging technology leads to new architectures integrating multiple sources of description of the image content. Indeed, addressing the problem of combining modalities for indexing and querying is of huge importance in forthcoming retrieval methodologies and is the only solution for achieving significant retrieval performance on image documents. This paper presents a multi-facetted conceptual framework integrating semantics, texture and spatial features for automatic image retrieval. It features a high-level representation formalism handling symbolic image descriptions and a unified full-text query framework. Experiments with queries combining multiple characterizations of the image content on a corpus of 2500 photographs validate our proposal.