¹Department of Computer Science and Technology, University of Science & Technology of China, Hefei, China
²Joint Research Lab of Excellence, CityU-USTC Advanced Research Institute, Suzhou, China
³Department of Computer Science, City University of Hong Kong, Hong Kong, China

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Abstract—We build a distance education application of a Chinese handwriting education system that allows students to do practice at anytime and anywhere. As an intelligent tutor, the system can automatically check the handwriting errors, such as the stroke production errors, stroke sequence error and stroke relationship error. Then our system should provide useful feedback to the student. In this paper, attributed relational graph matching is used to locate the handwriting errors. The pruning strategy is applied to reduce the computational time. The experiment results show that our proposal can handle more handwriting error cases than existing methods with a higher accuracy.

Index Terms—Chinese handwriting education, handwriting errors, automatic error detection, intelligent tutoring, attributed relational graph matching.

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Cite: Zhi-Hui Hu, Yun Xu, Liu-Sheng Huang, and Howard Leung, "A Chinese Handwriting Education System with Automatic Error Detection," Journal of Software vol. 4, no. 2, pp. 101-107, 2009.