Color Image Retrieval Using Intuitionistic Fuzzy Sets

In this paper, a new attempt is being made using Attanassov's intuitionistic fuzzy set theory for image retrieval. Intuitionistic fuzzy sets consider not only membership degree of belonging but also take into account the uncertainty involved in membership degree known as hesitation measure. Color features (expressed in various color representation systems), were intensively used (independently or jointly) during the last decade. We propose to revisit the use of color image contents as image descriptors through the introduction of fuzziness, which naturally arise from the imprecision or vagueness of the pixel color values and human perception. This has been applied in the HSV color space. Hue and value are two color features that are used to construct intuitionistic fuzzy sets; we construct twodimensional sets which are more suitable than one-dimensional ones. Another key aspect of our method is using fuzzy quantities as a similarity measure between two intuitionistic fuzzy sets instead of a real number due to the imprecision of the similarities. To show the robustness of the proposed method, many experiments with large databases are performed and the results show the high performance of finding similar images.

Keywords:

Intuitionistic fuzzy sets , image retrieval , similarity measure