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A Reinforced Road Detection Method in Complicated Environment

机译:复杂环境下的道路加固检测方法

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Road detection is the most fundamental part of autonomous vehicles. Noises caused by shadows and vehicles on the road have a great negative impact on the road detection. Our method improves the performance under the noisy environment by taking advantage of color information to determine the road curvature. A novel geometrical method is proposed in this paper to select the most matched curvature. A graph-based image segmentation algorithm is introduced to extract the road area which is not affected by shadows and vehicles on the road. A bilateral filter is presented to smooth images while preserving edges and to help detect continuous and perceptually clear road borders.
机译:道路检测是自动驾驶汽车的最基本部分。道路上的阴影和车辆引起的噪声对道路检测产生很大的负面影响。我们的方法通过利用颜色信息确定道路曲率来改善在嘈杂环境下的性能。本文提出了一种新颖的几何方法来选择最匹配的曲率。引入了基于图的图像分割算法,以提取不受道路阴影和车辆影响的道路区域。提出了一个双边过滤器,可在保留边缘的同时使图像平滑并帮助检测连续且在感知上清晰的道路边界。

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