A Method for Handwritten Chinese Stroke Extraction Based on Ambiguous-zone Detection
基于模糊区域检测的手写汉字笔画提取方法

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.