基于弹性网格混合特征的脱机手写维文识别  

RECOGNISING OFFLINE HANDWRITTEN UYGHUR TEXT BASED ON MIXED FEATURES OF ELASTIC MESH

作　　者：贾建忠 龚声蓉[2] 衣马木艾山.阿布都力克木 

机构地区：[1]乌鲁木齐职业大学信息工程学院,新疆乌鲁木齐830001 [2]苏州大学计算机科学与技术学院,江苏苏州215006 [3]国家数字化学习工程技术研究中心,湖北武汉430079

出　　处：《计算机应用与软件》2014年第9期172-176,共5页Computer Applications and Software

基　　金：国家自然科学基金项目(61170124)

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GSC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.

关 键 词：弹性网格 混合特征 归一化 聚类中心 可分性判据 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]