基于弹性网格混合特征的脱机手写维文识别

摘要

手写体维文识别技术的关键在于特征提取方法的选择。为探求一种可靠性高、可分性强的脱机手写维文特征提取方法，在分析现有方法的基础上，结合维吾尔文字词自身的特点，提出一种在局部特征上基于弹性网格区域笔划密度、方向分解特征，在全局特征上提取交叉点、环、弧形笔划、附加笔划、外围轮廓特征的混合特征提取方法。通过在IFN/ENIT标准数据库及自采样数据集的聚类分析实验，识别正确率分别达到85％、84．3％。结果表明，方法综合统计特征和结构特征提取的优点，具有较强的抗扰能力，可分性优于GS C法。%The key of recognition technology for offline handwritten Uyghur text is the selection of feature extraction method.In order toexplore a features extraction method for Uyghur text with high reliability and strong separability,based on analysing the existing methods andcombining the characteristics of the Uyghur word itself,we present a mixed features extraction method,which is based on the strokes densitiesin elastic mesh region and the directional feature decomposition in its local features,and extracts the features of the strokes of cross-points,rings and arcs as well as the additional strokes and peripheral contours in its global features.Through the cluster analysis experiments on bothIFN /ENIT benchmark database and self-sampling test set,its recognition correct rate reaches 85% and 84.3% separately.The resultsindicate that this method integrates the advantages of statistical feature and structural feature,has quite strong capability in anti-interference,and its separability is better than GSC method as well.