Stroke Correspondence Based on Graph Matching for Detecting Stroke Production Errors in Chinese Character Handwriting

People may make mistakes in writing a Chinese character. In this paper, we apply error-tolerant graph matching to find the stroke production errors in people's handwriting of Chinese characters. A set of edit operations to transform one graph into another are defined for achieving this purpose. The matching procedure is denoted as a search problem of finding the minimum edit distance. The A* algorithm is used to perform the searching. Experiments show that the proposed method outperforms existing algorithms in identifying stroke production errors. The proposed method can help in Chinese handwriting education by providing feedback to correct users who have stroke production errors in writing a Chinese character.

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