CBIR technique is becoming increasingly important in medical field in order to store, manage, and retrieve image data based on user query. Searching is done by means of matching the image features such as color, texture, shape, or different combinations of them. Texture features play an important role in computer vision, image processing and pattern recognition. In this paper we introduce a novel method of using IFS theory for CBIR using texture feature. Results obtained using IFS method is compared with fuzzy method and non-fuzzy method. Texture analysis is an important research field in computer vision, image processing and pattern recognition. Tamura proposed statistical features which corresponds to visual perception. We introduce a novel method of using IFS theory(along with the membership degree the hesitation degree is also take into account) for CBIR using texture feature.