Abstract
Regions of interest in photos are important clues for the content-based image retrieval. However, segmenting semantically meaningful objects in the photo automatically for the query and similarity matching is known to be an unsolved problem. As an alternative, in this paper, we propose a scheme to form a query region in the image space in terms of 4× 4 sub-images. The set of query sub-images, which include the region of interest in the image space, is used for the basic unit for the similarity matching. Specifically, the edge histogram descriptor and the color layout descriptor in MPEG-7 are used to extract image features in the chosen sub-images and are compared to those extracted from the test images in the database. Experimental results show that the proposed method can retrieve images with similar regions in the images, even if the background regions look quite different from each other.
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