A Novel Region-Based Image Retrieval Method Using Relevance Feedback Feng Jing, Bo Zhang, Fuzong Lin, Wei-Ying Ma, and Hong-Jiang Zhang   View Paper (PDF)   Return to IMAGE RETRIEVAL I Abstract Content-based image retrieval using region segmentation has been an active research area in the past few years. Contrasting to traditional approaches, which compute only global features of images, the region-based methods extract features of the segmented regions and perform similarity comparisons at the granularity of region. In this paper, we propose a novel region-based retrieval method, Self-Learned Region Importance (SLRI). In this method, image similarity measure is based on the region importance learned from users­¯feedback. The region importance that coincides with human perception can not only be used in a query session, but also be memorized and cumulated for future queries. Experimental results on a database of about 8,600 general-purposed images show the effectiveness of our method. DiSC'02 © 2003 Association for Computing Machinery