【作者】 白文荣；

【导师】 高光来；

【作者基本信息】 内蒙古大学 ， 计算机应用， 2007， 硕士

【摘要】 蒙古文输入法的研究开始于上世纪八十年代初期，主要集中在键盘输入上，对蒙古文文字识别的研究非常少。针对这种情况，我们提出研制一套手写体蒙古文字识别系统，为蒙古文提供了一种快速、高效、智能的输入方式。联机手写识别的根本任务是通过数字设备采集手写输入信号，从中提取输入特征，再与特征库加以匹配识别的过程。但是由于手写体笔迹变动非常大，精确识别比较困难。特别是连笔字的识别，由于字母切分的困难使得识别难度大增。近年来，随着个人数字助理(PDA)等便携式移动计算设备的普及，手写输入的应用越来越广泛。现在有很多汉字和英文的联机手写识别产品问世。而蒙古文字作为一种在蒙古族等少数民族地区流行的语言文字，研究它的手写识别方法对促进民族地区的信息与科技发展都是大有裨益的。本论文主要论述了联机手写蒙古文字识别技术。我们依次采用了去除噪声的预处理技术、基于蒙古文自身结构特征的基元切分技术、粗分类和细分类特征提取技术，以及结合了HMM模型与DTW方法的多分类器设计技术等。基于以上技术，我们开发出一个蒙古文字识别实验系统。实验结果表明，受训人员的单词正确识别率达到90％，笔迹受限的单词正确识别率达到83％。系统整体性能良好稳定，识别率初步达到实用化水平。更多还原

【Abstract】 In the 1980s, research of Mongolian characters input methods was begun. Most of input methods were concentrated on the keyboard code. But research of Mongolian characters recognition was quite little. Under the circumstances, we proposed to research and realize a recognition system for handwriting Mongolian characters, that can provide a new input method, which is quick, highly efficient and intelligent. The fundamental task of Online handwriting recognition is to take an input pattern, and the handwritten signals collected online via a digitizing device, and classify it as one of a pre-specified set of words (i.e., the system’s lexicon). Because of large variation of handwriting, exact recognition is very difficult. Especially the connectivity between the characters, make the recognition more difficult.During recent years, the application of online handwriting recognition is more and more widespread, mainly due to the increasing popularity of the personal digital assistant (PDA). Now there are many products of online handwriting recognition of Chinese characters and English characters. Mongolia language is very popular among the Mongolia people in the North China, so the research of online handwriting Mongolia words recognition has a far-reaching meaning about developing the Minority information technology and national culture.This paper primarily discussed Online Handwriting Recognition methods for Mongolia words. We used in turn preprocessing technology based on removing the noise、letter segmentation method based on the structure of Mongolian language、the feature selection technology which include coarse classification features and fine classification features, as well as Multiple Classifier which combined HMM model and the DTW method and so on. Based on the above technology, we developed a Mongolian writing recognition experiment system. Experimental results show that writer-dependent words achieve recognition rates above 90%. And unconstrained words achieve recognition rates above 83%. Our system run well, and the recognition rate initially achieves the practical level.更多还原