Symmetry-Based Indexing of Image Databases
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Abstract
The use of shape as a cue for indexing into pictorial databases has been traditionally based on global invariant statistics and deformable templates, on the one hand, and local edge correlation on the other. This paper proposes an intermediate approach based on a characterization of the symmetry in edge maps. The use of symmetry matching as a joint correlation measure between pairs of edge elements further constrains the comparison of edge maps. In addition, a natural organization of groups of symmetry into a hierarchy leads to a graph-based representation of relational structure of components of shape that allows for deformations by changing attributes of this relational graph. A graduated assignment graph matching algorithm is used to match symmetry structure in images to stored prototypes or sketches. The results of matching sketches and grey-scale images against a small database consisting of a variety of fish, planes, tools, etc., are promising.
