ROI-oriented image query and indexing for content-based retrieval

A new scheme for image query and indexing based on the concepts of region-of-interest (ROI) is proposed for content-based retrieval. Users are allowed to impose an ROI directly over the sample image, and the subsequent query is then focused on the content of selected ROI in order to find those images containing similar regions or objects from the database. To accomplish this objective, a neural network model, called a self-organizing map (SOM), is exploited to adaptively separate each image into several homogeneous regions without using any prior knowledge followed by a distance measure for ROI matching. Experimental results demonstrate that the proposed approach is fairly flexible, efficient and effective with great potential for further development