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Recognition of handwritten Bangla basic characters and digits using convex hull based feature set

机译:使用基于凸壳的功能集的手写BANGLA基本字符和位数

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In dealing with the problem of recognition of handwritten character patterns of varying shapes and sizes, selection of a proper feature set is important to achieve high recognition performance. The current research aims to evaluate the performance of the convex hull based feature set, i.e. 125 features in all computed over different bays attributes of the convex hull of a pattern, for effective recognition of isolated handwritten Bangla basic characters and digits. On experimentation with a database of 10000 samples, the maximum recognition rate of 76.86% is observed for handwritten Bangla characters. For Bangla numerals the maximum success rate of 99.45%. is achieved on a database of 12000 sample. The current work validates the usefulness of a new kind of feature set for recognition of handwritten Bangla basic characters and numerals.
机译:在处理对不同形状和大小的手写字符模式的识别问题时,选择适当的特征集是实现高识别性能的重要性。目前的研究旨在评估基于凸壳的功能集的性能,即,在图案的凸壳的不同托盘属性上计算的125个功能,以有效识别孤立的手写Bangla基本字符和数字。在实验与10000个样本的数据库中,对于手写的Bangla字符,观察到76.86%的最大识别率。对于Bangla数字,最大成功率为99.45%。在12000个样本的数据库中实现。目前的工作验证了一种新的功能集的有用性,以便识别手写的Bangla基本字符和数字。

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