IRFuM: Image Retrieval Via Fuzzy Modeling


  • Hossein Ajorloo
  • Abolfazl Lakdashti


Content based image retrieval, fuzzy rule base, fuzzy modeling


To reduce the semantic gap in the content based image retrieval (CBIR) systems we propose a fuzzy rule base approach. By submitting a query to the proposed system, it first extracts its low-level features and then checks its rule base for determining the proper weight vector for its distance measure. It then uses this weight vector to determine what images are more similar to the query image. For the training purpose, an algorithm is provided by which the system adjusts its fuzzy rules' parameters by gathering the trainers' opinions on which and how much the image pairs are relevant. For further improving the performance of the system, a feature space dimensionality reduction method is also proposed. We compared the proposed method with some other common ones. Our experiments on a subset of the Corel database containing 59 600 images show that the proposed method is more precise than these compared methods based on the precision and recall criterions.


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Author Biographies

Hossein Ajorloo

Department of Computer Engineering
Sharif University of Technology, Tehran, Iran

Abolfazl Lakdashti

University College of Rouzbahan, Sari, Iran




How to Cite

Ajorloo, H., & Lakdashti, A. (2012). IRFuM: Image Retrieval Via Fuzzy Modeling. COMPUTING AND INFORMATICS, 30(5), 913–941. Retrieved from