Volume 7 Number 7 (Jul. 2012)
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JCP 2012 Vol.7(7): 1733-1742 ISSN: 1796-203X
doi: 10.4304/jcp.7.7.1733-1742

Similarity measures for content-based image retrieval based on intuitionistic fuzzy set theory

Shaoping Xu, Chunquan Li, Shunliang Jiang
1School of Information Engineering, Nanchang University, NanChang, JiangXi, China
2Department of Systems and Computer Engineering, Carleton University, Ottawa, ON Canada, K1S 5B6


Abstract—In this paper, a new intuitionistic fuzzy model for images based on the HSV color histogram is proposed. The image can be treated as an Attanassov’s intuitionistic fuzzy set (IFS) with this new model. A new and simple calculation of similarity measurement called IFSL1 based on similarity measurement of intuitionistic fuzzy set L1 is presented. Unlike general fuzzy similarity measure that consider only the membership degree, the new intuitionistic similarity measure takes into account the membership degree, the nonmembership degree and the hesitation degree, these have been found to be highly useful in dealing with vagueness. The similarity measure IFSL1 is used for content-based image retrieval (CBIR).With the similarity measure IFSL1, image retrieval can be carried out more rapidly than with many other existing similarity measurements and the results better coincide with human perception.

Index Terms—Content-based image retrieval , Intuitionistic fuzzy set , Similarity measure , HSV color space , Image fuzzy model.

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Cite: Shaoping Xu, Chunquan Li, Shunliang Jiang, "Similarity measures for content-based image retrieval based on intuitionistic fuzzy set theory," Journal of Computers vol. 7, no. 7, pp. 1733-1742, 2012.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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