%0 Journal Article
%T Method for license plate detection based on improved AdaBoost algorithm<br>一种改进AdaBoost算法的车牌检测方法
%A FANG Yi-qiu
%A LU Dao-bing
%A GE Jun-wei
%A <br>方义秋
%A 卢道兵
%A 葛君伟
%J 计算机应用研究
%D 2009
%I 
%X Focusing on the disadvantages of classical AdaBoost algorithm, this paper mainly analyzed the issue that the training time for classifiers was time-consuming and in training process the sample weights were easily distorted and a new method was advanced to avoid the problems. The new method was to buffer the computational results of sorted feature values and regulate the updated rules of sample weights appropriately. As a result, using the method to train a cascade license plate, the experimental results show that the new method does not lead to the issue of weight distortion and time consuming like classical AdaBoost often does, and moreover, the training time is shortened to 50 percent with a high detection rate.
%K AdaBoost
%K weight distortion
%K time consuming
%K cascade classifier
%K license plate detection<br>AdaBoost算法
%K 权重扭曲
%K 耗时
%K 级联分类器
%K 车牌检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=A887F0D816E12F9D23A2797E7CDF4131&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=59906B3B2830C2C5&sid=76495C5AD8EDB77D&eid=CAAB4D9420DEB9C6&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=10