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基于HMM的分类器在联机手写藏文识别中的应用
  • 期刊名称:微电子学与计算机
  • 时间:0
  • 页码:98-101
  • 语言:中文
  • 分类:TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]西北民族大学中国民族信息技术研究院,甘肃兰州730030
  • 相关基金:国家自然科学基金项目(60273090)
  • 相关项目:语义检索和自动识别的唐卡图像知识库系统关键技术研究
中文摘要:

为了解决联机手写藏文识别中藏文的曲线型笔划比较多,连笔情况很普遍以及相似字丁多等问题,提出了一种新的联机手写藏文识别方法:基于HMM分类器的联机手写藏文识别的方法.设计了三种不同的HMM分类器进行藏文字丁识别,实验结果表明,基于HMM分类器的联机手写藏文识别具有较高地识别率,前十位识别率可达93.9012%.

英文摘要:

In order to solve Tibetan curve strokes to be quite many, is very common including the situation where the Ti- betan character is written in a nonstop manner and many similar Tibetan characters in on-line recognition of handwritten Tibetan characters, we proposed a new method of on-line recognition of handwritten Tibetan characters: an on-line recog- nition of handwritten Tibetan characters method based on HMM classifiers. We designed three kinds of different HMM classifiers to distinguish Tibetan characters, the experimental results show that HMM-based classifiers on-line recognition of handwritten Tibetan characters has higher recognition rate, recognition rate of the first ten characters reach 93. 9012%.

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