基于笔画曲率特征的笔迹鉴别方法

现有的手写汉字脱机笔迹鉴别方法存在只能针对特定字符或需要大量样本字符等问题,为此提出一种基于笔画曲率特征的笔迹鉴别方法。首先运用数学形态学对采集的笔迹图像进行预处理,在横、竖、撇、捺四个方向提取具有代表性的笔画骨架,然后对笔画骨架进行圆的重构,提取四个方向笔画圆的曲率作为特征值组成笔迹特征矩,根据待鉴别的笔迹特征矩与数据库中笔迹特征矩向量夹角相似性度量结果对样本做出判断。实验结果表明该文方法对于待鉴别样本字符的内容没有要求,样本字符数量要求低、应用范围广、鲁棒性强。

Method of Writer Identification Based on Curvature of Strokes

The popular offline writer identification methods for handwritten Chinese characters usually work on some specific characters and demand a huge number of training samples. In this paper, a writer identification method based on curvature detection of skeletal stroke is proposed. Firstly, images of handwritten characters are preprocessed by mathematical morphology, and the representative skeletal strokes are extracted in the four directions of horizontal, vertical, left-falling and right-falling. Then, the circle reconstruction is applied to the extracted skeletal strokes, and the curvatures of the stroke circle in four directions are selected to form the handwriting features. Finally, the characters are identified according to the angular similarity. Experimental results show that the proposed algorithm makes no restrictions on the content of the character to be identified and requires less training samples.