Shape representation by spatial partitioning for content based retrieval applications

Shape representations for classification or retrieval purposes, have been extensively investigated, but only a few methods have tried to represent shapes as extended entities without reducing them to their boundary profiles or to synthetic geometric descriptors. An original solution for shape representation is proposed; it relies on a modelling technique originally developed to express directional spatial relationships between extended spatial entities. The representation selects a discrete set of points with respect to which a relationship matrix is computed, accounting for the spatial distribution of shape pixels. This is accomplished at different levels of resolution by a tree based structural representation. Properties of the representation and a measure of shape similarity are discussed. The efficiency and effectiveness of the proposed solution have also been assessed in the context of content based retrieval applications, through an experimental evaluation using a shape collection.