Block-diagonal form of distance matrix for region-based image retrieval

There are two substantial open issues in the field of the image retrieval: semantic gap between computationally extracted low-level features and human operated high-level concepts, and high retrieval speed independent from the volume of the database. Search of the images on the level of objects or regions (segmentation) is a step towards semantic-based retrieval. In this paper we propose a new cluster-like indexing algorithm in metric space which preliminary transforms distance matrix into block-diagonal form and ensures the minimum number of matches at the retrieval stage. This form can be used separately or embedded into existent indexing methods.