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An Approach for Lane Segmentation in Traffic Monitoring Systems

机译:交通监控系统中的车道分割方法

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This paper describes an approach for lane segmentation in traffic monitoring systems based on road region and lane line information. Firstly, we use Gaussian background modeling algorithm to extract the motion regions and background image, then lane region can be acquired by region growing algorithm based on motion regions. The straight-lines about lane lines can be acquired by using Hough transform on the edge image of background. Finally we divide a road area into several lane regions by fusing the trajectories information of vehicles acquired by KLT method. The experiments in deferent scenes show the efficiency and robustness of the proposed approach.
机译:本文介绍了一种基于道路区域和车道线信息的交通监控系统中的车道分割方法。首先,我们使用高斯背景建模算法提取运动区域和背景图像,然后通过基于运动区域的区域增长算法来获取车道区域。通过在背景的边缘图像上使用霍夫变换可以获取关于车道线的直线。最后,通过融合通过KLT方法获取的车辆的轨迹信息,将道路区域划分为几个车道区域。在不同场景下的实验表明了该方法的有效性和鲁棒性。

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