Abstract
Search effectiveness in an image database is always a trade-off between the indexing cost and semantic richness. A solution that provides a significant degree of semantic richness that simultaneously limits the indexing cost is presented. The query schemes are able to enhance the query speed by adopting a semantically rich structured form for high-level image content information, as well as exploiting the efficiency of conventional database search. Through the use of rules, which can be either pre-defined or dynamically incorporated, a new level of semantic richness can be established, which will eliminate the costly detailed indexing of individual concepts. The query algorithm incorporates rule-based conceptual navigation, customized weighting, incremental indexing and relevance feedback mechanisms to enhance retrieval effectiveness.
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Sutanto, D., Leung, C.H.C. (1999). Automatic Index Expansion for Concept-Based Image Query. In: Huijsmans, D.P., Smeulders, A.W.M. (eds) Visual Information and Information Systems. VISUAL 1999. Lecture Notes in Computer Science, vol 1614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48762-X_50
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DOI: https://doi.org/10.1007/3-540-48762-X_50
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