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一种模板匹配和神经网络的车牌字符识别方法
引用本文:王敏,黄心汉,魏武,李炜.一种模板匹配和神经网络的车牌字符识别方法[J].华中科技大学学报(自然科学版),2001,29(3):48-50.
作者姓名:王敏  黄心汉  魏武  李炜
作者单位:华中科技大学控制科学与工程系
基金项目:湖北省重点科学技术发展计划项目!(991PO111),武汉市重点科技攻关计划资助项目!(2 0 0 0 10 10 0 94)
摘    要:提出了一种基于模板匹配和神经网络的车牌识别方法。该方法集成了模板匹配识别车牌字符和神经网络识别车牌字符的优势,可有效地提高车牌字符的识别率、识别速度和识别系统的泛化能力。实验结果表明:大多数情况下,该方法的识别率超过90%,识别时间不超过1200ms,能有效地识别各种车牌中的字符,满足实际系统的要求。

关 键 词:车牌字符识别  模板匹配  神经网络  集成  识别率  识别速度  识别系统
文章编号:1000-8616(2001)03-0048-03
修稿时间:2000年4月13日

A Method of Characters in Vehicle Number-plate Using Pattern Match and Neural Networks
Wang Min,Huang Xinhan,Wei Wu,Li Wei.A Method of Characters in Vehicle Number-plate Using Pattern Match and Neural Networks[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,2001,29(3):48-50.
Authors:Wang Min  Huang Xinhan  Wei Wu  Li Wei
Abstract:A method of characters in vehicle number plate using pattern match and neural networks is presented. This method integrates the advantages of pattern match and neural networks recognizing characters in vehicle number plate. It can be used to solve at the same time the problem that only pattern match or neural network is difficult to recognize the characters. The recognition rate can be improved with the recognition time reduced and the adaptable ability of recognition method increased. The experimental results show that, for a vehicle number plate, recognition rate of characters is more than 90% and the recognition time of characters is less than 1.2 second by using this method. It is obvious that this method is of more effective recognition ability than other methods.
Keywords:vehicle character recognition  pattern match  neural networks  integration
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