A Region-Based Image Retrieval Approach Using Block DCT

This paper proposes a region-based image retrieval approach using block discrete cosine transform (BDCT). In our retrieval system, for simplicity, an image is equally divided into four regions and an additional central region with one fourth size of the image. Therefore, an image is represented by five segmented regions, each of which is associated with a feature vector derived from BDCT. Users can select any region as the main theme of the query image. The relevance between a query image and any database image is ranked according to a similar measure computed from the selected regions between two images. For those images without distinctive objects and scenes, users can still select the whole image as the query condition. The experimental results show that our approach is easy to identify main objects and reduce the influence of background in the image, and thus improve the performance of image retrieval.