四川大学学报（自然科学版）Issue(4)：775-780,6.DOI:10.3969/j.issn.0490-6756.2013.04.021
基于贝叶斯网络分类器的车牌相似字符识别
Recognition of similar characters on license plate based on bayesian network classifiers
摘要
Abstract
The low recognition rate of similar characters will affect the performance of the whole car plate recognition system ,but similar characters differ from each other mostly in a local part ,also the numbers of samples are different ,so those classifiers used now have unstable performance .The Bayesian Net-work Classifier has stable performance by making full use of and combining prior knowledge with sample information no matter how many samples and features . T housands of test samples are used to test Bayesian Network Classifier as well as other classifiers .The experiment result shows that ,using the same features ,the Bayesian Networks Classifier has a relatively high recognition rate and stable per-formance on similar character recognition compared with AdaBoost classifier ,BP Neural network classi-fier and SVM classifier .关键词
车牌识别/相似字符/特征提取/贝叶斯网络分类器Key words
license plate recognition/similar character/feature extraction/bayesian network classifier分类
信息技术与安全科学引用本文复制引用
黄文琪,吴炜,苏力思,吴晓红..基于贝叶斯网络分类器的车牌相似字符识别[J].四川大学学报（自然科学版）,2013,(4):775-780,6.
