摘要
提出了一种基于AdaBoost的车牌字符自动识别算法。AdaBoost是一种构建准确分类器的学习算法,它将一族弱学习算法通过一定规则结合成为一个强学习算法,从而通过样本训练得到一个识别准确率理想的分类器,将之用于车牌字符识别,对车牌图像进行实验,对车牌字符样本进行特征提取,用特征来训练有效分类器,用MATLAB完成了对车牌照数字识别的模拟,结果证实此算法对车牌字符识别有一定准确性,具有良好的效果。
A method of License Plate Recognition using AdaBoost algorithm is presented.AdaBoost is a learning algorithm for constructing accurate classifiers, It can obtain a strong learning algorithm by combining a series of weak learning algorithms through some rules, which is used on License Plate Recognition, Selecting character features, trains the effective classifier with features, simulates the recognition in use of MATLAB, the result of simulation indicated that the method of this paper proposed has the good effect.
出处
《微计算机信息》
北大核心
2007年第22期262-264,共3页
Control & Automation
基金
广东省教育厅自然科学基金(z03032)
关键词
车牌识别
字符识别
特征选择
ADABOOST
License Plate Recognition, character recognition, Characteristic Choosing, AdaBoost