Abstract—In this paper, a new system of fuzzy relevance feedback for image retrieval is introduced. In conventional CBIR systems, the users are restricted to make a binary labeling on the retrieval results, while this determination is difficult for rich images in semantic. In the proposed system, we accumulate user interactions using a soft feedback model to construct Fuzzy Transaction Repository (FTR). The repository remembers the user’s intent and, therefore, in terms of the semantic meanings, provides a better representation of each image in the database. To best exploit the benefits of user feedback, we improved the proposed system, so that the repository remembers the user’s intent in a suitable manner (as structure-based fuzzy transaction repository) and provides an accurate representation for each image in the database. The semantic similarity between the query and each database image can then be computed using the current feedback and the semantic values in the FTR. Furthermore, feature re-weighting is applied to the session-term feedback in order to learn the weight of low-level features. These two similarity measures are normalized and combined together to form the overall similarity measure. Our experimental results show that the average precision of the proposed systems exceeds 83% after three iterations.

Index Terms—Feature Re-weighting, Fuzzy Relevance Feedback, Fuzzy Transaction Repository, Image Retrieval

M. Javidi is with the Machine Vision Lab from Computer Engineering Department of Ferdowsi University of Mashhad, Mashhad, Iran. (e-mail: malihejavidi@ gmail.com).
H.R. Pourreza is with Computer Engineering Department of Ferdowsi University of Mashhad, Mashhad, Iran. (phone: (+98) 511 876 3306; fax: (+98) 511 862 6541; e-mail: hpourreza@ um.ac.ir).
H. Sadoghi Yazdi Author is with Computer Engineering Department of Ferdowsi University of Mashhad, Mashhad, Iran. (phone: (+98) 511 876 3306; fax: (+98) 511 862 6541; e-mail: h_sadoghi@ um.ac.ir)

Cite: Malihe Javidi, Hamid Reza Pourreza and Hadi Sadoghi Yazdi, "A Semantic Feedback Framework for Image Retrieval," International Journal of Computer and Electrical Engineering vol. 2, no. 3, pp. 417-425, 2010.