CAJ | 학술논문

　　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。
　　개소료사충경전적필적변연제취산법，통과실험결과분석득출Sobel산자재제취유오이문필적변연시효과교호。제출일충여문본무관、특정융합적필적감별방법，융합적특정포괄개진망격창구미결구특정화필적곡향특정，해방법채용개솔밀도분포적방법통계필적적망격창구미결구특정화곡향특정，감별효과체도료예기치。개소일사고신적도상처리기술，제출대경전산자적개진、융합이급파신적도상처리기술운용도유문적필적감별공작중장시하일보적주요임무。
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.