基于表示法的道路目标和车道信息高效提取

Jaehyoung Yu, Youngjoon Han, H. Hahn
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引用次数: 10

摘要

鲁棒可靠的车道检测是驾驶辅助系统和自动驾驶系统的重要问题。从移动车辆上的摄像机获取的输入图像需要进行处理,以便进行车道和车辆交通检测。我们提出了一种算法,该算法使用链码检测器来检测车道,并使用图像边缘车辆形成的水平线来检测车辆。第一步,利用canny边缘算子对链码进行分析,得到车道两侧的消失点;第二步,结合消失点和行驶车辆两侧的车道信息确定车道。我们定义了车道属性和可靠车道检测的极限条件。复杂背景图像的实验结果验证了该算法的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient Extraction of On-Road Object and Lane Information Using Representation Method
Robust and reliable lane detection is an important issue for driver assistance systems and self-guided systems. Input images acquired from a camera on moving vehicle need to be processed for lane and vehicular traffic detection. We propose an algorithm that uses a chain code detector for detecting lanes and detects vehicles using the horizontal lines formed by the vehicles at the edge of the images. In the first step, a vanishing point is obtained from both sides of the lane, which are obtained from the chain code analysis using the canny edge operator. In the second step, the driveways are decided by combining the vanishing point and the lane information on both sides of the moving vehicle. We define the lane properties and the limiting conditions for reliable lane detection. The robustness of proposed algorithm has been verified from experimental results of complex background images.
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