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Weighted-function based algorithm for retrieving handwriting trajectory from off-line data

机译:基于加权功能从离线数据检索手写轨迹的算法

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Individuality of handwriting is the reason why it is used as a common base element for detecting character traits of the writer. It is believed that dynamic information improve the accuracy of the analysis, but they are not contained in an offline handwritten text. In order to recover dynamic information, a novel approach for handwriting trajectory recovery is proposed in this paper. The procedure is based on computing the objective function, which depends on parameters such as the angle of movement, path length, air pen tip movements, etc. The analysis is performed in MATLAB program package, using the text samples from IAM-OnDB database. The experimental results indicate that the average effectiveness of the proposed algorithm is above 75%.
机译:手写的个性是它用作用于检测作者字符特征的公共基本元件的原因。据信,动态信息提高了分析的准确性,但它们不包含在离线手写文本中。为了恢复动态信息,本文提出了一种用于手写轨迹恢复的新方法。该过程基于计算目标函数,这取决于运动角度,路径长度,空气笔尖端运动等的参数。使用来自IAM-ONDB数据库的文本样本在MATLAB程序包中执行分析。实验结果表明,所提出的算法的平均有效性高于75%。

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