基于Rough集的车牌字符识别方法  

Method for the recognition of vehicle license plate characters based on the rough set theory

作　　者：刘泓[1] 方敏[1] 梁朝军[1] 

机构地区：[1]合肥工业大学电气与自动化工程学院,安徽合肥230009

出　　处：《合肥工业大学学报（自然科学版）》2004年第10期1196-1200,共5页Journal of Hefei University of Technology：Natural Science

基　　金：安徽省自然科学基金资助项目(01042310)

摘　　要：提出了基于Rough集理论的车牌字符识别方法。该方法根据训练样本的特征向量建立决策表,应用Rough集理论对决策表属性进行约简,从约简后的决策表中获取决策规则,按照规则可信度的大小进行规则的匹配。实验表明该方法有效减少了决策属性的个数,提高了规则的泛化程度,简化了规则匹配算法,在车牌字符识别中取得了较好的识别效果。A method for the recognition of vehicle license plate characters is presented based on the rough set theory. The features of the training samples are extracted to build up the decision table. The rough set theory is applied to reduce the decision attributes of the table. Then the decision rules can be generated from the reduced decision table. The rule-match algorithm is based on the creditability of the rules. The application examples have showed a good result in the recognition of the vehicle's plate characters. The reduced decision attributes are beneficial to the improvement of the generality of the rules and the simplification of rule matching.

关 键 词：ROUGH集 字符识别 规则匹配 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]