Design and evaluation of spatial similarity approaches for image retrieval
Similarity retrieval by spatial image content (i.e. using multiple objects and their relationships in space) is still an open problem which has received considerable attention in the literature. The most powerful approaches of spatial image content representation and matching are attributed relational graphs (ARGs) and symbolic projections (e.g. two-dimensional 2D strings). A framework is proposed for studying the performance of spatial similarity approaches in image databases (IDBs). The classical ARG and 2D string matching methods are evaluated. Several variants of ARG and 2D string methods for improving their accuracy and speeding-up their time responses are also proposed and evaluated. A critical analysis of the performance of all these methods is presented. The analysis indicates that in retrieving images by spatial content, retrieval response time and accuracy are traded-off.
image retrieval attributed relational graphs 2d strings image database spatial relationships