A. Grbavec, Dept. of Comput. & Inf. Sci., Queen's Univ., Kingston, Ont., Canada
D. Blostein, Dept. of Comput. & Inf. Sci., Queen's Univ., Kingston, Ont., Canada
This paper investigates graph rewriting as a tool for high-level recognition of two-dimensional mathematical notation. "High-level recognition" is the process of determining the meaning of a diagram from the output of a symbol recognizer. Characteristic problems of high-level mathematics recognition include: determining the groupings of symbols into recursive subexpressions and resolving ambiguities that depend upon global context. Our graph-rewriting approach uses knowledge of the notational conventions of mathematics, such as operator precedence and operator range, more effectively than syntactic or previous structural methods. Graph rewriting offers a flexible formalism with a strong theoretical foundation for manipulating two-dimensional patterns. It has been shown to be a useful technique for high-level recognition of circuit diagrams and musical scores. By demonstrating a graph-rewriting strategy for mathematics recognition, this paper provides further evidence for graph rewriting as a general tool for diagram recognition, and identifies some of the issues that must be considered as this potential is explored.
Index Terms:
rewriting systems; image recognition; pattern recognition; mathematics recognition; graph rewriting; high-level recognition; mathematical notation; symbol recognizer; recursive subexpressions; global context; operator precedence; operator range; two-dimensional patterns manipulation; notational conventions; circuit diagrams; musical scores; diagram recognition
Citation:
A. Grbavec, D. Blostein, "Mathematics recognition using graph rewriting," icdar, vol. 1, pp.417, Third International Conference on Document Analysis and Recognition (ICDAR'95) - Volume 1, 1995