一种结合光流和阴影去除的交通流量检测系统

Zhaoxiang Zhang, Yuqing Hou, Yunhong Wang, Jie Qin
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引用次数: 9

摘要

交通流检测在智能交通系统中起着重要的作用。基于视频的交通流量检测系统是智能交通系统中应用最广泛的策略。在这种情况下,本文设计并实现了一个基于视频的交通流量检测系统MyTD。MyTD同时利用阴影去除和光流算法。首先介绍了智能交通系统的发展现状,重点介绍了基于视频的交通检测技术,这是智能交通系统的关键。其次,提出了一种结合RGB和HSV色彩空间信息的阴影去除算法。第三,在迭代金字塔LK光流算法的基础上,利用OpenCV实现了车辆跟踪功能,以及连接部件标记功能和车辆计数功能。最后,基于上述算法对MyTD进行了实现和测试。实验结果表明,与传统的光流算法相比,该方法具有优异的性能。
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A traffic flow detection system combining optical flow and shadow removal
Traffic flow detection plays an important role in Intelligent Transportation Systems(ITS). Video based traffic flow detection system is the most widely used strategy in ITS. Under this circumstance, we design and implement a video based traffic flow detection system which is called MyTD in this paper. MyTD takes advantages of both shadow removal and optical flow algorithms. Firstly, we introduce the current development of ITS and focus on the video based traffic detection technology, which is the key to ITS. Secondly, a shadow removal algorithm combining information in both RGB and HSV color spaces is proposed. Thirdly, based on the Iterative Pyramidal LK Optical Flow Algorithm, a vehicle tracking function is realized by OpenCV, as well as a Connected Components Labeling function and the vehicle counting function. Finally, MyTD is implemented and tested based on the algorithm presented above. Experimental results show the outstanding performance of our method comparing with traditional optical flow algorithms.
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