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The recognition of Roman hand-written characters using dynamic information recovery

机译:使用动态信息恢复识别罗马手写字符

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The use of temporal information such position, velocity and acceleration has led on-line systems to achieve better performance than off-line systems. Some research has been undertaken in order to transform the off-line problem into an on-line one. The paper shows that the Chinese postman's paradigm can successfully be used to extract consistent sub-stroke ordering in Roman writing. An algorithm called optimal trace recovering (OTR) is presented which incorporates the Chinese postman's paradigm and is shown to produce an optimal writing trace with respect to minimum stroke length and deviation at special (cross and fork) points. The OTR algorithm produces an acceptable consistency in recovering the writing trace for each writer and furthermore the method described is computational fast and robust. Dynamic features has been extracted from the directed graph produced by the OTR algorithm and used by a statistical classifier. On average, recognition rates of 91.64% (first choice) and 94.55% (first two choices) has been achieved.
机译:使用时间信息这样的位置,速度和加速度的使用,在线系统中实现了比离线系统更好的性能。已经进行了一些研究,以便将离线问题转换为一线电路。论文表明,中国邮递员的范式可以成功地用于提取罗马写作中一致的子行程排序。提出了一种称为最佳追踪恢复(OTR)的算法,该算法包含了中国邮递员的范例,并且被示出了相对于最小行程长度和特殊(交叉和叉)点的偏差产生最佳写入轨迹。 OTR算法在恢复每个作家的写入跟踪时,OTR算法产生可接受的一致性,此外,所描述的方法是计算快速且坚固的方法。动态特征已从OTR算法产生的定向图中提取,并由统计分类器使用。平均而言,已达到91.64%(首选)和94.55%(前两种选择)的识别率。

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