Indexing based on edit-distance matching of shape graphs

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Abstract
We are investigating a graph matching approach for indexing into pictorial databases using shock graphs, a symmetry- based representation of shape. Each shape (or a collection of edge elements) is represented by a shock graph. Indexing of a query into a pictorial database is accomplished by comparing the corresponding shock graph to the graphs representing database elements and selecting the best match. This paper introduces a new metric for comparing shock graphs.
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