介绍了四种经典的笔迹边缘提取算法,通过实验结果分析得出Sobel算子在提取维吾尔文笔迹边缘时效果较好。提出一种与文本无关、特征融合的笔迹鉴别方法,融合的特征包括改进网格窗口微结构特征和笔迹曲向特征,该方法采用概率密度分布的方法统计笔迹的网格窗口微结构特征和曲向特征,鉴别效果达到了预期值。介绍一些高新的图像处理技术,提出对经典算子的改进、融合以及把新的图像处理技术运用到维文的笔迹鉴别工作中将是下一步的主要任务。
This paper introduces four classical edge extraction algorithms of handwriting. The analysis of the experimental result shows that Sobel operator in edge extraction of Uyghur handwriting is better. It proposes a text-independent method of handwrit- ing identification based on feature fusion. Feature fusion includes mesh-window microstructure feature and curvature-direction feature. This method adopts probability density distribution to count the mesh-window microstructure features and the curvature- direction features. The identification effect reaches the expected value. It introduces some new image processing technology, and puts forward the improvement and the fusion of the classical algorithms and new processing technology applied to the Uyghur handwriting identification will be the next step major job.