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基于PSO-IFCM的遮挡车牌车辆识别
引用本文:浦雅雯,刘万军,姜文涛.基于PSO-IFCM的遮挡车牌车辆识别[J].计算机工程,2012,38(14):157-160.
作者姓名:浦雅雯  刘万军  姜文涛
作者单位:1. 辽宁工程技术大学电子与信息工程学院,辽宁葫芦岛,125105
2. 辽宁工程技术大学软件学院,辽宁葫芦岛,125105
基金项目:国家自然科学基金资助项目
摘    要:针对智能交通系统中车辆类型自动识别问题,利用车辆面积、车窗位置和车轮位置3个特征,实现车辆类型的快速分类识别。对聚类中心初始化和模糊聚类算法进行改进,提出基于粒子群优化的改进模糊C均值算法(PSO-IFCM)的识别方法,用于车牌遮挡情况下的车辆识别。实验结果表明,PSO-IFCM算法具有较好的鲁棒性。

关 键 词:车牌识别  车型识别  聚类中心  特征提取  粒子群优化  模糊C均值
收稿时间:2011-10-18

Identification of Vehicle with Block License Plate Based on PSO-IFCM
PU Ya-wen , LIU Wan-jun , JIANG Wen-tao.Identification of Vehicle with Block License Plate Based on PSO-IFCM[J].Computer Engineering,2012,38(14):157-160.
Authors:PU Ya-wen  LIU Wan-jun  JIANG Wen-tao
Affiliation:a(a.School of Electronics and Information Engineering;b.School of Software,Liaoning Technical University,Huludao 125105,China)
Abstract:Aiming at the problem of vehicle types automatic identification of vehicle recognition system,this paper designs a more perfect vehicle type fast classification and identification method by using vehicles characteristics of area,window position and the wheel position.An identification method based on Particle Swarm Optimization-Improved Fuzzy C-means(PSO-IFCM) algorithm is presented by improving the clustering center initialization and fuzzy clustering algorithm,and is used in block license plate of the vehicle identification in Intelligent Transportation System(ITS).Experimental results indicate that PSO-IFCM algorithm has better robustness and feasibility in the traffic regulation.
Keywords:license plate recognition  vehicle type recognition  clustering center  feature extraction  Particle Swarm Optimization(PSO)  Fuzzy C-means(FCM)
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