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Fuzzy aggregation operators in region-based image retrieval

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3 Author(s)
Z. Stejic ; Dept. of Comput. Intelligence & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan ; Y. Takama ; K. Hirota

We examine the effect of the fuzzy aggregation operators on the image retrieval performance, by empirically comparing 67 operators, applied to the problem of computing the image similarity, given a collection of feature similarities of the image regions. While majority of the existing image similarity models express the image similarity as an aggregation of feature similarities, no study presents a systematic comparison of the different operators. We compare the 67 operators by: (1) incorporating each operator into a hierarchical, region-based similarity model, which expresses the image similarity as an aggregation of region similarities, and each region similarity as an aggregation of the corresponding feature similarities; and (2) evaluating the obtained model(s) on five test databases, containing 64,339 general-purpose images, in 749 semantic categories. Results show that the retrieval performance strongly depends on the operator(s) incorporated in the similarity model - the difference in the average retrieval precision between the best and the worst performing of the 67 operators is up to 50%.

Published in:

Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on  (Volume:3 )

Date of Conference:

25-29 July 2004