On-line Chinese character recognition with attributed relational graph matching

Abstract

A structural method for on-line recognition of Chinese characters is proposed, which is stroke order free and allows variations in stroke type and stroke number. Both input characters and the model characters are represented with complete attributed relational graphs (ARGs). An optimal matching measure between two ARGs is defined. Classification of an input character can be implemented by inexactly matching its ARG against every ARG of the model base. The matching procedure is formulated as a search problem of finding the minimum cost path in a state space tree, using the A^* algorithm. In order to speed up the search of the A^*, besides a heuristic estimate, a novel strategy that utilizes the geometric position information of strokes of Chinese characters to prune the tree is employed. The efficience of our method is demonstrated by the promising experimental results.