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19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06) (2006)
Salt Lake City, Utah
June 22, 2006 to June 23, 2006
ISSN: 1063-7125
ISBN: 0-7695-2517-1
pp: 881-886
Agma J. M. Traina , University of S?o Paulo at S?o Carlos , Brazil
Joselene Marques , University of S?o Paulo at S?o Carlos , Brazil
Caetano Traina Jr. , University of S?o Paulo at S?o Carlos , Brazil
ABSTRACT
This paper introduces two novel relevance feedback techniques that integrate a new way to implement the query center movement with a suitable weighting on the similarity function. These techniques integrated to a content-based image retrieval (CBIR) system, improves the precision of the results when using texture features up to 42%, and employing at most 5 iterations. Thus, the user satisfaction with the system is increased as our experiments demonstrated. <p>Besides being effective, the new RF techniques are very fast as they take less than one second to reprocess the queries at each iteration. The experiments also show that with three iterations the users are satisfied with the query results, and the major gain in precision happens in the first iteration, achieving improvements of up to 30%, what lessens the user efforts and anxiety.</p>
INDEX TERMS
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CITATION

J. Marques, A. J. Traina and C. Traina Jr., "Fighting the Semantic Gap on CBIR Systems through New Relevance Feedback Techniques," 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)(CBMS), Salt Lake City, Utah, 2006, pp. 881-886.
doi:10.1109/CBMS.2006.88
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