面向书写教学的手写汉字图像笔画还原
Stroke Retrieval of Handwritten Chinese Character Images for Handwriting Teaching

摘要 为了实现智能化汉字书写教学, 提出一种手写汉字图像的笔画还原方法。首先提取手写汉字图像的骨架; 然后从知识工程的角度出发, 利用字形中稳定的拓扑信息, 消除骨架中的歧义变形; 最后利用A* 算法建立并求解手写汉字与相应模板汉字的字形相似度模型, 从而分割出手写汉字图像中的各个笔画, 并输出它们与模板汉字中各个笔画的对应关系。此方法的笔画还原结果可以应用于手写汉字规范性的自动化评判等场合。
Abstract For intelligent teaching of Chinese character handwriting, the authors present a stroke retrieval method for handwritten Chinese character images, which includes three steps. Firstly, the method extracts the skeletons from the handwritten image. Secondly, from the perspective of knowledge engineering, it eliminates the skeleton distortions by using the stable grapheme topology. Thirdly, it divides the skeletons into some strokes and outputs the matching relationship between them and the strokes in the template character, by building and solving the similarity model with A* algorithm. The result of the method can be used to automatic quality assessment for handwritten Chinese character images.