摘要
字符识别是车牌识别的一个关键环节。在对车牌字符集进行深入分析的基础上,提出了形状特征向量等概念,从理论上分析并证明了形状特征向量用于车牌字符识别的可行性。文中提出了一种基于形状特征向量的车牌字符识别算法,并进行了仿真实验。实验结果表明,形状特征向量能够用作车牌字符识别,基于形状特征向量的车牌识别算法具有97.31%的正确率;此外,该算法没有复杂的训练过程,不需要大量数据来记录训练结果,实现简单,是一种轻量级的车牌字符识别算法。
Character recognition is the key step of vehicle license plate recognition(VLPR).Some concepts,such as shape feature vector(SFV),were proposed after examining the character set used by vehicle license plate and the feasibility of using SFV to recognize vehicle license plate characters was proven theoretically.Then,a character recognition algorithm of vehicle license plate was proposed and evaluated by simulation.The result of the simulation shows that SFVcan be used as license plate character recognition,and the license plate recognition algorithm based on SFV has an accuracy rate of 97.31%.Besides,this algorithm has no complex training process and does not require large amounts of data to record the training results.It is simple to implement and is a lightweight license plate character recognition algorithm.
作者
马李昕
李凤坤
MA Li-xin;LI Feng-kun(Dalian Neusoft University of Information,Dalian,Liaoning 116023,China)
出处
《计算机科学》
CSCD
北大核心
2019年第B06期239-241,258,共4页
Computer Science
基金
辽宁省博士启动基金(20170520398)
辽宁省教育厅科学技术一般项目(L2015041)资助
关键词
车牌识别
字符识别
形状特征向量
Vehicle license plate recognition
Character recognition
Shape feature vector
