A framework for linguistic relevance feedback in content-based image retrieval using fuzzy logic

Authors:
Ronald R. Yager;Frederick E. Petry
Affiliations:
Machine Intelligence Institute, Iona College, 715 North Avenue, New Rochelle, NY and Department of EE and CS, Tulane University, New Orleans, LA;Department of EE and CS, Tulane University, New Orleans, LA
Venue:
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Dealing with uncertainty in data mining and information extraction
Year:
2005

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Abstract

We describe a new approach for exploiting relevance feedback in content-based image retrieval (CBIR). In our approach to relevance feedback we try to capture more of the users' relevance judgments by allowing the use of natural language like comments on the retrieved images. Using methods from fuzzy logic and computational intelligence we are able to reflect these comments into new targets for searching the image database. Such enhanced information is utilized to develop a system that can provide more effective and efficient retrieval.