›› 2013, Vol. 26 ›› Issue (11): 22-.

• 论文 • 上一篇    下一篇

一种基于SVM的改进车牌识别算法

薛丹,孙万蓉,李京京,贾海龙,杨子峰,王政   

  1. (西安电子科技大学 电子工程学院,陕西 西安 710071)
  • 出版日期:2013-11-15 发布日期:2013-11-19
  • 作者简介:薛丹(1988—),女,硕士研究生。研究方向:图像信号处理。E-mail:362237087@qq.com。孙万蓉(1960—),女,教授。研究方向:数据采集与传输技术,图像信号处理。

An Improved Method of Car License Plate Recognition Based on SVM

XUE Dan,SUN Wanrong,LI Jingjing,JIA Hailong,YANG Zifeng,WANG Zheng   

  1. (School of Electronic Engineering,Xidian University,Xi'an 710071,China)
  • Online:2013-11-15 Published:2013-11-19

摘要:

提出了一种基于支持向量机(SVM)的改进车牌识别方法。对细化处理后的字符采用网格、水平投影与垂直投影密度的特征提取方法,保证了字符整体与局部特征,同时也使特征向量集的维数充分低。结合3种特征提取方法得到的特征向量集,采用 SVM进行车牌号码识别。对于易混淆字符,提出了根据各自的特征进行2次识别的算法,该算法有效解决了易混淆字符误识别的问题。实验结果表明,该算法鲁棒性好、抗干扰能力强、识别率达到了98.58%。

关键词: 车牌识别, SVM, 特征向量, 网格, 投影, 细化

Abstract:

An improved recognition method of license plate based on support vector machine (SVM) is proposed in this paper.The features of grid,horizontal projection and vertical projection density are extracted after character thinning treatment.The feature vector set of three features has overall and local features of the characters,and low dimension.Based on SVM,plate numbers are recognized through feature vector sets.For confusing characters,a second recognition algorithm is put forward according to their respective features,which solves the problem of confused character recognition efficiently.Experiment results show that the algorithm has good robustness,strong anti-jamming ability,and a high recognition rate to 98.58%.

Key words: license plate recognition;SVM;feature vector;grid;projection;thin

中图分类号: 

  • TP391