An Image Clustering and Feedback-based Retrieval Framework

Most existing object-based image retrieval systems are based on single object matching, with its main limitation being that one individual image region object can hardly represent the user's retrieval target, especially when more than one object of interest is involved in the retrieval. Integrated Region Matching IRM has been used to improve the retrieval accuracy by evaluating the overall similarity between images and incorporating the properties of all the regions in the images. However, IRM does not take the user's preferred regions into account and has undesirable time complexity. In this article, we present a Feedback-based Image Clustering and Retrieval Framework FIRM using a novel image clustering algorithm and integrating it with Integrated Region Matching IRM and Relevance Feedback RF. The performance of the system is evaluated on a large image database, demonstrating the effectiveness of our framework in catching users' retrieval interests in object-based image retrieval.

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