针对手写汉字笔画提取的重点和难点——模糊区域的识别和解析问题，提出了一种新的基于模糊区域检测的笔画提取算法。该算法首先利用细化算法提取的fork候选点和fork候选点附近的轮廓信息来检测模糊区域；然后利用图模型来对子笔画和模糊区域进行建模，同时通过构造贝叶斯分类器来分析子笔画对的连续性，并通过路径搜索来得到子笔画序列；最后通过进行B样条插值来提取细化后的笔画。对比实验结果表明，该算法不仅能够有效地用于模糊区域检测和笔画提取，而且能够避免细化结果在模糊区域内的形状畸变。

To effectively identify and interpret ambiguous zones in handwritten Chinese image,a new method for handwritten stroke extraction based on ambiguous-zone detection is proposed.In the method,a candidate set of fork points are extracted using a thinning algorithm,and the ambiguous zones are detected according to the fork points and the contour beside them.Then,the sub-strokes and ambiguous zones can be modeled with a graph,and a Bayesian classifier is built to analyze the continuity of sub-stroke pairs.Finally,sequences of sub-stroke are achieved by searching paths in the graph,and thinned strokes can be retrieved by B-spline interpolation.Experimental results show that the proposed method is effective and accurate for both ambiguous-zone detection and stroke extraction compared to other methods and reduce the shape distortions in ambiguous zones to an acceptable level.