一种改进的基于视频的车辆检测与识别方法  

Improved Video Based Vehicle Detection and Identification Method

作　　者：魏武[1] 龚树锋[1] 龚树超[2] 

机构地区：[1]华南理工大学自动化科学与工程学院,广东广州510640 [2]北京邮电大学信息与通信工程学院,北京100876

出　　处：《计算机测量与控制》2010年第1期20-22,共3页Computer Measurement &Control

摘　　要：为了提高基于视频的车辆检测技术在应用中的实时性和准确率,提出了一种应用单目视觉进行车辆检测的方法;首先,提取车道边缘,由车道边缘得到道路区域,根据经验知识在车道区域内确定感兴趣区域,减少车辆检测算法搜索范围;接着基于车辆的对称性特征,阴影和边缘特征对兴趣区域进行过滤,进一步缩小感兴趣区域;最后用离线训练好的AdaBoost分类器对过滤后的图像进行分类识别,检测出动态的车辆;实验结果表明,利用该算法能满足实时性和准确性的要求。In order to improve the real-time and accuracy of the vehicle detection technology in the application, it shows a vehicle detection method based on monocular vision. First of all, extract the edge of lane, obtain the driveway area from the edge of the road, confirm the region of interest with the experiences in the driveway area, it can reduce the scope for searching. Then filter the region of interest based on the symmetry, the shadow and the edge of the car and narrow the region of interest even more. Finally, classify the filtered images with the AdaBoost classifier which is trained off-line, detect those motorial vehicles. The experimental results show that the algorithm ean adapt to the real-time and accuracy requirements.

关 键 词：机器视觉 车辆检测 道路区域 分类器 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]