Spatial similarity measures for multimedia applications

Abstract

Similarity based retrieval of images is an important task in multimedia applications. A major class of users queries require retrieving those images in the database that are spatially similar to the query image. To process these queries, a spatial similarity function is desired. A spatial similarity function assesses the degree to which the spatial relationships in a database image conform to those specified in the query image. In this paper, we formalize the notion of spatial similarity for 2D symbolic images and provide a framework for characterizing the robustness of spatial similarity algorithms with respect to their ability to deal with translation, scale, rotation (both perfect and multiple) variants as well as the variants obtained by an arbitrary composition of translation, scale, and rotation. This characterization in turn is useful for comparing various algorithms for spatial similarity systematically. As an example, a few spatial similarity algorithms are characterized and then experimentally contrasted using a testbed of images.