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Reducing user log size in an inter-query learning content based image retrieval (CBIR) system with a cluster merging approach

Chung, K.P., Wong, K.W. and Fung, C.C. (2006) Reducing user log size in an inter-query learning content based image retrieval (CBIR) system with a cluster merging approach. In: 2006 International Joint Conference on Neural Networks, 16-21 July 2006, Vancover, B.C, Canada pp. 1184-1191.

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    Link to Published Version: http://dx.doi.org/10.1109/IJCNN.2006.246825
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    Abstract

    Use of relevance feedback (RF) in the feature vector model has been one of the most popular approaches to fine tune query for content-based image retrieval (CBIR) systems. This paper proposes a framework that extends the RF approach to capture the inter-query relationship between current and previous queries. By using the feature vector model, this approach avoids the need of memorizing actual retrieval relationship between the actual image indexes and the previous queries. This implies that the approach is more suitable for image database application where images are frequently added and removed. The proposed inter-query relationship is presented using a data cluster that is defined by a transformation matrix, a centroid point and the reference boundary value. These parameters are captured in a file commonly known as the user log. The file however will grow rapidly after successive retrieval sessions. In order to reduce the size of the user log, this paper introduces a merging approach to combine clusters that are close-by and similar in their characteristics. Experiments have shown that the proposed framework has out performed the short term learning approach and yet without the burden of the complex database maintenance strategies required in long-term learning approach.

    Publication Type: Conference Paper
    Murdoch Affiliation: School of Information Technology
    Publisher: IEEE
    Copyright: (c) 2006 IEEE.
    Notes: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    URI: http://researchrepository.murdoch.edu.au/id/eprint/600
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