Online Chinese character recognition using attributed relational graph matching

A structural method for online recognition of Chinese characters is proposed which is stroke-order free and allows variations in stroke type and stroke number. and the model characters 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. To speed up the search of the A*, in addition to a heuristic estimate, a novel strategy that utilises the geometric position information of strokes of Chinese characters to prune the tree is employed. The efficiency of the method is demonstrated by the promising experimental results.