An efficient handwritten Devnagari character recognition system using neural network

N. Sahu, N. K. Raman
{"title":"An efficient handwritten Devnagari character recognition system using neural network","authors":"N. Sahu, N. K. Raman","doi":"10.1109/IMAC4S.2013.6526403","DOIUrl":null,"url":null,"abstract":"Character recognition systems for various languages and script has gain importance in recent decades and is the area of deep interest for many researchers. Their development is strongly integerated with Neural Networks. But, recognizing Devanagari Script is relatively greater challenge due to script's complexity. Various techniques have been implemented for this problem with many improvements so far. This paper describes the development and implementation of one such system comprising combination of several stages. Mainly Artificial Neural Network technique is used to designed to preprocess, segment and recognize devanagari characters. The system was designed, implemented, trained and found to exhibit an accuracy of 75.6% on noisy characters.","PeriodicalId":403064,"journal":{"name":"2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMAC4S.2013.6526403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

Abstract

Character recognition systems for various languages and script has gain importance in recent decades and is the area of deep interest for many researchers. Their development is strongly integerated with Neural Networks. But, recognizing Devanagari Script is relatively greater challenge due to script's complexity. Various techniques have been implemented for this problem with many improvements so far. This paper describes the development and implementation of one such system comprising combination of several stages. Mainly Artificial Neural Network technique is used to designed to preprocess, segment and recognize devanagari characters. The system was designed, implemented, trained and found to exhibit an accuracy of 75.6% on noisy characters.
基于神经网络的手写体Devnagari字符识别系统
近几十年来,各种语言和文字的字符识别系统变得越来越重要,并且是许多研究人员感兴趣的领域。它们的发展与神经网络紧密结合。但是,由于梵文的复杂性,识别梵文是一个相对更大的挑战。到目前为止,针对这个问题已经实现了各种技术,并进行了许多改进。本文描述了一个这样的系统的开发和实现,该系统由几个阶段组成。主要采用人工神经网络技术对汉字进行预处理、分割和识别。经过设计、实现、训练,该系统对噪声字符的识别准确率达到了75.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信