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一种基于新特征的车牌检测方法
引用本文:江林升,朱学芳. 一种基于新特征的车牌检测方法[J]. 计算机工程与应用, 2011, 47(20): 188-190. DOI: 10.3778/j.issn.1002-8331.2011.20.053
作者姓名:江林升  朱学芳
作者单位:1.南京森林警察学院 信息系,南京 210046 2.南京大学 信息管理系,南京 210093
摘    要:车牌检测是车牌识别的关键所在,两种新的区域统计学特征能迅速排除大量的非车牌区域,在此基础上,采用增加了辅助判决的级联分类器来改进AdaBoost算法。实验表明,该算法与基于颜色特征分类器和传统的级联AdaBoost分类器相比,具有较快的检测速度、较高的检测率和较低的误检率。

关 键 词:特征  级联分类器  AdaBoost  
修稿时间: 

Car plate detection based on new features
JIANG Linsheng,ZHU Xuefang. Car plate detection based on new features[J]. Computer Engineering and Applications, 2011, 47(20): 188-190. DOI: 10.3778/j.issn.1002-8331.2011.20.053
Authors:JIANG Linsheng  ZHU Xuefang
Affiliation:1.Department of Information,Nanjing Forest Police College,Nanjing 210046,China 2.Department of Information Management,Nanjing University,Nanjing 210093,China
Abstract:License plate detection is the key to the recognition of automatic license plates.The two new regional statistics can quickly rule out a large number of non-regional plate vehicles, based on which, a noval Adaboost with auxiliary detection is proposed in the paper.Tests show that compared with color-based classifier and traditional cascaded AdaBoost classifier, the new algorithm takes the advantages of a faster detection speed,a higher detection rate as well as fewer false detections.
Keywords:feature  cascaded classifier  AdaBoost
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