书写顺序恢复是从静态文本图像中提取动态的字符书写顺序信息，将2维的图像转换为1维的书写位置的时间序列的过程。为了对手写汉字进行书写顺序提取，提出了一种脱机手写汉字书写顺序的恢复模型。该模型首先将汉字分为整字、部件、子部件和笔画4个层次；然后利用4种拆分操作将整字拆分为部件，再将部件拆分为子部件；最后通过定义一组拆分关系与子部件偏序关系之间的对应规则来得到子部件的全序关系。而将子部件作为最基本的恢复单位，其书写顺序可通过对笔画和交叉笔画对进行分类来得到。实验表明，该模型提出的汉字书写顺序恢复方法的恢复结果具有较高的准确率，且处理速度达到了6.9字/s。

The objective of recovering writing order is to extract dynamic handwriting information from static text images, which can be seen as to convert a 2-dimensional image into sequences of 1-dimensional vectors of pentip positions along the time axis. This paper proposes a model for recovering writing order from offline handwritten Chinese character. In this model, a 4-layer hierarchy is presented to model each Chinese character, where character, component, subcomponent and stroke are located at each layer, respectively. Characters are decomposed into components and each component is decomposed to subcomponents in turn by four decomposing operators. The totally-ordered relations between subcomponents are retrieved by defining the corresponding rules between decomposed relations and a poset of subcomponents. Subcomponents are the basic recovering primitives in this model, whose writing orders are recovered by classifying strokes and pairs of crossing strokes. Experimental results show that the proposed method is effective and accurate.