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An Approach to Stroke-Based Online Handwritten Bangla Character Recognition

机译:一种基于中风的在线手写孟加拉字符识别方法

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This paper deals with stroke-based online Bangla character recognition strategy. In the present work, constituent strokes have been extracted from characters and then popularly used distance based features have been estimated in order to recognize the basic strokes. Next, a rule-based approach is followed for the recognition of the characters from the previously recognized strokes. A total of 15,000 isolated online handwritten Bangla characters contributing 32,534 stroke samples have been used in this experiment, and a satisfactory result of 89.39% recognition accuracy has been achieved.
机译:本文涉及基于笔划的在线Bangla字符识别策略。在本工作中,组成笔画已经从字符中提取,然后估计了普遍使用的基于距离的特征,以识别基本笔画。接下来,遵循基于规则的方法,用于识别先前识别的笔划中的字符。在该实验中使用了贡献32,534中风样本的突出的15,000个孤立的网上手写鲍拉人物,达到了89.39%的识别准确性的令人满意的结果。

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