一种结合两种视觉算法的可靠道路车道检测方法

R. Labayrade, S. Leng, D. Aubert
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引用次数: 19

摘要

本文提出了一种基于视觉的可靠车道检测方法。单个使用的传感器是机载正面单眼单色相机。新颖之处在于通过使用几个(本文中是两个)独立的算法来引入冗余。通过将它们的输出组合在一起,我们获得了更可靠的结果以及结果可靠性的置信度值。当置信度较低时,将对算法进行初始化,以避免误检。第一种算法计算纵向相干结果,第二种算法计算横向相干结果。首先,介绍了每种算法,然后描述了它们的输出组合方式。我们还讨论了这两种算法如何相互作用。然后,在实时环境下的实验强调了这种方法所提供的改进,并表明结果是相关的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A reliable road lane detector approach combining two vision-based algorithms
We present a new approach for detecting road lane with reliability using vision-based techniques. The single used sensor is an on-board frontal monocular monochromic camera. The novelty is to introduce redundancy by using several (two in this paper) independent algorithms. By combining their outputs together, we obtain more reliable results as well as a confidence value about the reliability of the results. When the confidence value is low, an initialization of the algorithms is performed to avoid false detection. The first algorithm computes longitudinal-coherent results, whereas the second algorithm computes lateral-coherent results. First, each algorithm is presented and then the way in which their outputs are combined is described. We also discuss how the two algorithms interact together. Then, experiments in a real-time context underline the improvements provided by this approach and show that results are relevant.
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