Efficient image retrieval with multiple distance measures

There is a growing need for the ability to query image databases based on image content rather than strict keyword search. Most current image database systems that perform query by content require a distance computation for each image in the database. Distance computations can be time consuming, limiting the usability of such systems. There is thus a need for indexing systems and algorithms that can eliminate candidate images without performing distance calculations. As user needs may change from session to session, there is also a need for run-time creation of distance measures. In this paper, we introduce FIDS, or ''Flexible Image Database System.'' FIDS allows the user to query the database based on user-defined polynomial combinations of predefined distance measures. Using an indexing scheme and algorithms based on the triangle inequality, FIDS can return matches to the query image without directly comparing the query image to much of the database. FIDS is currently being tested on a database of eighteen hundred images.