Reading #16: An Efficient Graph-Based Symbol Recognizer (Lee)

Summary
In this paper, the author introduces a new method for graph-based symbol recognition. Each stroke is first recognized as a basic primitive shape and then feature values are computed for each stroke relative to each other stroke in the symbol. The four features used are relative length of a stroke, number of intersections, angle of intersection, and relative position of intersection. 6 error metrics are then weighted and summed to determine the match percentage of an unknown symbol to a template.

Discussion
The author uses four different method to match individual strokes from an unknown symbol to a template symbol. Three of these methods are based on search algorithms and the fourth is a sorting method based on locations of the primitives. While the fourth method was much faster, it often provided less accurate graph matching. Since the fourth method was orders of magnitude faster, it could perhaps be combined with one of the search methods and may help to reduce the run time for the search method if run after the sort method.