SVM在车牌字符识别中的应用  

Application of SVM to character recognition of vehicle license plate

作　　者：吴进军[1] 杜树新[1] 

机构地区：[1]浙江大学工业控制技术国家重点实验室浙江大学工业控制研究所浙江,杭州310027

出　　处：《电路与系统学报》2008年第1期84-87,共4页Journal of Circuits and Systems

摘　　要：采用支持向量机方法实现车牌字符识别。根据车牌字符排列特征,构造了汉字、数字、字母、数字+字母4个最佳分类器,通过车牌字符的序号对每个字符进行对应识别,再将识别结果组合得到车牌号码。实验结果表明该方法具有较高的车牌字符整体识别率,达到了98.33%,识别时间仅为15ms,能够满足实际应用。Support Vector Machine （SVM） is used to recognize the characters of vehicle license plates. According to the arrayed feature of the plates, four types of classifying systems, including Chinese characters classifying system, letter classifying system, figure ＆ letter classifying system, figure classifying system, are configured. Every character in a vehicle license plate would be recognized by the corresponding classifying system according to its sequence number in the plate. The experimental result of 120 vehicle license plate images shows high recognition rate of 98.33% and fast speed of 15 milliseconds for all characters of a vehicle license plate.

关 键 词：支持向量机 车牌字符识别 排列特征 识别组合 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]