基于遗传算法的笔画匹配方法

Hao Bai, Xiwen Zhang
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引用次数: 3

摘要

对于外国留学生来说,用数字笔书写汉字是一种自然的方式,他们的笔迹信息比数字图像丰富得多。笔画匹配是分析汉字书写错误的前提。由于学习者的写作素质和特点存在很大差异,目前的研究很难对日益增长的规模和复杂性给出最优的解决方案。本文提出了一种基于遗传算法的笔画匹配方法。适应度函数的构造考虑了汉字的结构特点和书写特点。在实验中,该方法的正确匹配笔画率至少达到90.17%,表明该方法在后续的笔迹错误分析中是有效的。
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A method of matching strokes based on genetic algorithm
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.
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