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

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.