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%.
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%.
出处
《微电子学与计算机》
CSCD
北大核心
2009年第4期98-101,104,共5页
Microelectronics & Computer
基金
国家自然科学基金项目(60273090)
关键词
联机手写藏文识别
隐马尔可夫模型
HMM分类器
识别率
on-line recognition of handwritten Tibetan characters
Hidden Markov Models（HMM）
HMM-based classitiers
recognition rate
作者简介
梁弼（1982-），硕士研究生．研究方向为图像处理与模式识别．王维兰 女，（1961-），教授．研究方向为图像处理与模式识别、数据挖掘、藏文信息处理．钱建军 男，（1983-），硕士研究生．研究方向为图像处理与模式识别．
