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Image Retrieval using Conceptual Fuzzy Sets
Tomohiro Takagi*, Kazushi Kawase* and Kazuhiko Otsuka**
*Department of Computer Science, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki-shi, Kanagawa 214-8571, Japan
**Department of Electronics and Information Science, Tsukuba College of Technology, 4-3-15 Amakubo, Tsukuba-shi, Ibaragi 305-0005, Japan
Received:October 19, 2000Accepted:November 15, 2000Published:November 20, 2000
Keywords:Image retrieval, Fuzzy sets
Abstract
An algorithm is described that uses fuzzy sets to handle word ambiguity, the main cause of vagueness in the meaning of a word. It is based on conceptual fuzzy sets (CFSs), which represent the meaning of words by linking other related words. A trial application of this algorithm to image retrieval showed that it can retrieve images that conceptually fit the meanings of the entered keyword based on the context understood from the characteristics of images. Experimental results showed that the proposed algorithm works well to represent various meanings of a keyword by linking it to other words and to connect words directly to image data. In addition, image retrieval starting with a sample image also worked well. First, a selected sample image was translated into abstract concepts, and images fitting the concepts were chosen.
Cite this article as:T. Takagi, K. Kawase, and K. Otsuka, “Image Retrieval using Conceptual Fuzzy Sets,” J. Adv. Comput. Intell. Intell. Inform., Vol.4 No.6, pp. 450-456, 2000.Data files:
