  In this paper, we introduce an approach to overcome the low accuracy of the
Content-Based Image Retrieval (CBIR) (when using the global features). To
increase the accuracy, we use Harris-Laplace detector to identify the interest
regions of image. Then, we build the Region-Based Image Retrieval (RBIR). For
the efficient image storage and retrieval, we encode images into binary
signatures. The binary signature of a image is created from its interest
regions. Furthermore, this paper also provides an algorithm for image retrieval
on S-tree by comparing the images' signatures on a metric similarly to EMD
(earth mover's distance). Finally, we evaluate the created models on COREL's
images.
