A method of matching strokes based on genetic algorithm
Hao Bai, Xiwen Zhang · 2016
It is natural way to write Chinese characters by digital pen for foreign students, whose handwriting information is much richer than digital image. Stroke matching is the prerequisite to analyze handwriting errors of Chinese character. Present research hardly delivers the optimal solution of the problem on the growing sizes and complexity because of wide differences among learners' writing qualities and features. This paper proposes an approach based on genetic algorithm to match strokes. Construction of fitness function considers structural and writing features of Chinese characters. The method can achieve correct matching stroke rate 90.17% at least in the experiments, which indicates that our proposed approach Is effective In next steps of handwriting errors analysis.