Image Retrieval Based On Regions Of Interest
Arbitrary-shaped queries; Image indexing and retrieval; Image processing; Regions of interest
Query-by-example is the most popular query model in recent content-based image retrieval (CBIR) systems. A typical query image includes relevant objects (e.g., Eiffel Tower), but also irrelevant image areas (including background). The irrelevant areas limit the effectiveness of existing CBIR systems. To overcome this limitation, the system must be able to determine similarity based on relevant regions alone. We call this class of queries region-of-interest (ROI) queries and propose a technique for processing them in a sampling-based matching framework. A new similarity model is presented and an indexing technique for this new environment is proposed. Our experimental results confirm that traditional approaches, such as Local Color Histogram and Correlogram, suffer from the involvement of irrelevant regions. Our method can handle ROI queries and provide significantly better performance. We also assessed the performance of the proposed indexing technique. The results clearly show that our retrieval procedure is effective for large image data sets.
IEEE Transactions on Knowledge and Data Engineering
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Source API URL
Vu, Khanh; Hua, Kien A.; and Tavanapong, Wallapak, "Image Retrieval Based On Regions Of Interest" (2003). Scopus Export 2000s. 1694.