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一种基于新特征的车牌检测方法 被引量:2

Car plate detection based on new features
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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。 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.
出处 《计算机工程与应用》 CSCD 北大核心 2011年第20期188-190,共3页 Computer Engineering and Applications
关键词 特征 级联分类器 ADABOOST feature cascaded classifier AdaBoost
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