用于车牌字符识别的SVM算法  

SVM for Chinese Character Recognition in License Plate

作　　者：王晓光[1] 王群[1] 

机构地区：[1]北京理工大学电子工程系,北京100081

出　　处：《现代电子技术》2004年第8期8-10,共3页Modern Electronics Technique

摘　　要：支持向量机 ( SV M)是 2 0世纪 90年代初由 Vapnik等人提出的一类新型机器学习方法 ,此方法能够在训练样本很少的情况下达到很好的分类推广能力。本文应用 SV M算法对车牌中的汉字字符进行识别 ,无字符特征提取提高了识别速度 ,并且可得到较高的识别率。实验讨论了 SV M算法用于字符识别时 ,不同的核函数对识别率的影响。实验结果表明 ,用 SVSupport vector machines (SVM) is a kind of new machine learning method proposed by Vapnik and his team in 1990s This method gains a better generalization ability with a few of training examples An application of SVM algorithm in license plate character recognition is proposed in this paper Without extracting features of the characters, it can obtain quick result and high recognition rate Different kernel functions are discussed in this paper The experimental results show the feasibility and efficiency of this method

关 键 词：支持矢量机(SVM) 车牌字符识别 最优分类面 核函数 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]