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Target search in Content-Based Image Retrieval (CBIR) systems refers to finding a specific (target) image such as a particular registered logo or a specific historical photograph. Existing techniques, designed around query refinement based on Relevance Feedback (RF), suffer from slow convergence, and do not guarantee to find intended targets. To address these limitations, the authors propose several efficient query point movement methods. They prove that their approach is able to reach any given target image with fewer iterations in the worst and average cases. They propose a new index structure and query processing technique to improve retrieval effectiveness and efficiency. They also consider strategies to minimize the effects of users' inaccurate RF.
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