An Image Clustering and Retrieval Framework Using Feedback-Based Integrated Region Matching
Liping Zhou, Chengcui Zhang, Wen Bo Wan, Jeffrey B. Birch, Wei-Bang Chen · 2009
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. In this paper, 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 reflecting users' retrieval interests in object-based image retrieval.