Fuzzy queries in multimedia database systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Some approaches to best-match file searching
Communications of the ACM
Proximity Matching Using Fixed-Queries Trees
CPM '94 Proceedings of the 5th Annual Symposium on Combinatorial Pattern Matching
Selecting Good Keys for Triangle-Inequality-Based Pruning Algorithms
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
A Flexible Image Database System for Content-Based Retrieval
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Proceedings of the ACM International Conference on Image and Video Retrieval
An examplar-based approach for texture compaction synthesis and retrieval
IEEE Transactions on Image Processing
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There is a growing need for the ability to query image databases based on similarity of image content rather than strict keyword search. As distance computations can be expensive, there is 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.We have designed and implemented a prototype database system that allows a user a great deal of flexibility in runtime distance measure creation. FIDS, or "Flexible Image Database System," uses an indexing scheme and algorithms based on the triangle inequality. FIDS has been tested on a database of thirty seven thousand images and can often return results without directly comparing the query image to more than a small percentage of the original database. In this paper, we briefly summarize the technical contributions of FIDS and present a set of experiments that thoroughly evaluates the FIDS techniques and systems.