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Recognize Online Handwritten Bangla Characters Using Hausdorff Distance-Based Feature

机译:使用基于Hausdorff距离的功能识别在线手写的Bangla字符

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In this paper, an effort has been made to emphasize the usefulness of Hausdorff Distance (HD) and Directed Hausdorff Distance (DHD) based features for the recognition of online handwritten Bangla basic characters. Every character sample is divided into N number of rectangular zones and then HD- and DHD-based features have been computed from every zone to every other zone. These distance measurements are served as feature values for the present work. Experiment has been done on a set of 10,000 character dataset. Multilayer Perceptron (MLP) produces the best result with an accuracy of 95.57% when sample character is divided into 16 rectangular zones and DHD-based procedure has been considered.
机译:在本文中,已经努力强调Hausdorff距离(HD)的有用性,并指导了基于Hausdorff距离(DHD)的特征,以识别在线手写的Bangla基本角色。 每个字符样本都分为n个矩形区域,然后从每个区域计算HD和基于DHD的特征到每个其他区域。 这些距离测量作为本工作的特征值。 实验已经在一组10,000个字符数据集中完成。 多层的Perceptron(MLP)产生最佳结果,精度为95.57%,当样本字符分为16个矩形区域和基于DHD的程序时,已经考虑了。

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