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Handwritten Devanagari Compound Character Recognition Using Legendre Moment: An Artificial Neural Network Approach

机译:使用Legendre矩的手写体梵文复合字符识别:人工神经网络方法

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Handwritten Devanagari Compound character recognition is one of the new challenging task for the researcher, because Compound character are complex in structure, they are written by combination two or more character. Their occurrence in the script is up to 12 to 15%. In this research paper, a recognition system for handwritten Devanagari Compound Character is proposed bases on Legendre moment feature descriptor are used to recognize. Moment function have been successfully applied to many pattern recognition problem, due to this they tends to capture global features which makes them well suited as feature descriptor. The process image is normalized to 30X30 pixel size divided into zone, from this structural as well as statistical feature are extracted from each zone. The proposed system is trained and tested on 27000 handwritten collected from different people. For classification we have used Artificial Neural Network. The overall recognition rate for basic is up to 98.25% and for all compound character is 98.36%.
机译:手写梵文复合字符识别是研究人员一项新的挑战性任务,因为复合字符结构复杂,它们是由两个或多个字符组合而成的。它们在脚本中的出现率高达12%到15%。本文基于Legendre矩特征描述符,提出了一种手写梵文复合字符识别系统。矩函数已成功应用于许多模式识别问题,因此,它们倾向于捕获全局特征,这使其非常适合用作特征描述符。将过程图像规格化为30X30像素大小,将其划分为区域,并从每个区域中提取该结构以及统计特征。所提议的系统在从不同人那里收集的27000个手写体上经过培训和测试。对于分类,我们使用了人工神经网络。基本的整体识别率高达98.25%,所有复合字符的整体识别率为98.36%。

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