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首页> 外文期刊>Procedia Computer Science >A Robust Lane Detection Method Based on Vanishing Point Estimation
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A Robust Lane Detection Method Based on Vanishing Point Estimation

机译:基于消失点估计的鲁棒车道检测方法

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Although lane detection technology has been developed for decades, however, many challenging issues remain unresolved. In this paper, we propose a robust vanishing point-based lane detection method. Due to the perspective effect, the two parallel straight lines in 3-D space intersect at the 2-D plane. For the lane line extraction, we use lane shape features to extract lane lines. Firstly, we use LSD (line segment detectors) to extract the straight line segments in each frame of image. Secondly, we use a direction priority search method to remove the most of the interference information. This algorithm makes reference to the directional and shape features of lane lines in 2-D images. Finally, using the remaining straight line segments after filtering out the noise straight line to calculate the vanishing point of the lane line, we use a score function to remove non-candidate lane markings, the score function is constructed using the shape features, direction of the line segments. The experimental results show that the validity and robustness of our new algorithm under complex structured road scenes.
机译:尽管车道检测技术已经发展了几十年,但是,许多具有挑战性的问题仍未解决。在本文中,我们提出了一种基于消失点的鲁棒鲁棒检测方法。由于透视效应,3-D空间中的两条平行直线在2-D平面处相交。对于车道线提取,我们使用车道形状特征提取车道线。首先,我们使用LSD(线段检测器)提取图像每一帧中的直线段。其次,我们使用方向优先级搜索方法来删除大部分干扰信息。该算法参考了二维图像中车道线的方向和形状特征。最后,在滤除噪声直线后使用剩余的直线段计算车道线的消失点,我们使用得分函数删除非候选车道标记,该得分函数是使用形状特征,方向线段。实验结果表明,该算法在复杂结构化道路场景下的有效性和鲁棒性。

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