一种面向“互联网+”智能交通管理的车辆类型识别方法  

A vehicle type identification method oriented for "Internet+" intelligent traffic management

作　　者：吕林涛[1] 李志勋[2] 吕晖[3] 袁琴琴[1] 高环[4] 

机构地区：[1]西京学院信息工程学院,陕西西安710123 [2]西安航天动力试验技术研究所,陕西西安710100 [3]中国建筑西北设计研究院有限公司,陕西西安710018 [4]西安理工大学计算机科学与工程学院,陕西西安710048

出　　处：《现代电子技术》2017年第13期184-186,共3页Modern Electronics Technique

基　　金：国家自然科学基金(61273271);国防科工局"十二五"技术基础项目(JSJL2014203B015);陕西省工业科技攻关项目(2016GY-141);西京学院教改规划课题(JGGH1704)资助

摘　　要：针对现有智能交通管理中车辆类型识别方法存在分类器效率较低等诸多问题,通过构造一种新的分类器,建立了一种智能交通车辆类型识别新方法。首先采用边缘梯度直方图进行图像特征提取,然后通过融合纠错编码技术和K-近邻分类器构造新分类器实现车辆类型的分类。通过大量实验仿真分析比对表明,该方法不仅能将多类分类问题转化成多个两分类问题,而且使车辆类型识别效率提高了2%,鲁棒性好。因此,该方法在"互联网+"智能交通管理中具有广阔的应用前景和推广价值。Since the available vehicle type identification methods of the intelligent traffic management have various problems,such as low classifier efficiency,a new classifier was constructed to establish a vehicle type identification method for intelligent traffic.The edge gradient histogram is used to extract the image characteristics. The error correction coding technology and K-nearest neighbor classifier are fused to construct the new classifier to classify the vehicle types. The analysis and comparison results of a large number of experimental simulation show that the method can transform the multi-class classification problem into the multiple binary classification problem,make the vehicle type identification efficiency increased by 2%,and has the characteristic of good robustness. The method used in ″Internet＋″ intelligent traffic management has broad application prospect and high promotion value.

关 键 词：边缘方向直方图 纠错编码 K-近邻分类器 智能交通 车辆类型识别 

分 类 号：TN911-34[电子电信—通信与信息系统] TP391.4[电子电信—信息与通信工程]