Improving Image Retrieval Effectiveness in Query-by-Example Environment

Query-by-example is the most popular query model for today’s image retrieval systems. A typical query image contains not only relevant objects (e.g., Eiffel Tower), but also irrelevant image areas (e.g., the background). The latter, referred to as noise in this paper, has limited the effectiveness of existing image retrieval systems. We present here a similarity model for noise-free queries (NFQs), and investigate indexing techniques for this new environment. Our query model is more expressive than the standard query-byexample. The user can draw a contour around a number of objects to specify spatial (relative distance) and scaling (relative size) constraints among them, or use separate contours to disassociate these objects. Our experimental results confirm that traditional approaches, such as Local Color Histogram and Correlogram, suffer from noisy queries. In contrast, our method can leverage NFQs to offer significantly better performance. This is achieved using only a frac...

• Type: Conference
• Year: 2003
• Where: SAC
• Authors: Khanh Vu, Kien A. Hua, Ning Jiang
• Keywords: Applied Computing, Image Retrieval System, Query Model, SAC 2003, Typical Query Image