Region-based image retrieval

This paper presents a region-based method which uses multiple regions as the key to retrieve images. The proposed method represents the semantics or concepts embedded in the input images with three ingredients. One is a set of regions with weighted importance; the second is the corresponding feature distributions of the regions and the last is the spatial relationships between these regions. The importance of each segmented region in the input example images can be automatically and efficiently determined through a formulated linear system. In addition, a novel method for matching the spatial relationship between regions is also presented to capture the structural semantics of the content of images. By combining the feature distributions and the spatial relationships of regions with appropriate weights, the experimental results show that the retrieval results are much more accurate than other methods which utilize low-level features, such as color, texture, shape, and so on.