基于计算机视觉的直道和弯道多车道检测

Yan Jiang, F. Gao, Guoyan Xu
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引用次数: 77

摘要

采用“估计-检测”方法设计了一种结构化高速公路多车道视觉检测系统。它检测车辆行驶的车道(中央车道),并估计两个相邻车道的可能位置。然后根据这些估计进行检测。首先通过GPS定位和OpenStreetMap数字地图识别车辆是在直线道路上行驶还是在弯道上行驶。这两个案件的处理方式不同。对于直线道路,采用霍夫变换在原图像中检测中心车道,并设计一种简化的透视变换进行估计。对于曲线路径,进行完整的透视变换,通过扫描俯视图图像的每一行来检测中心车道。该系统能够检测到不清晰甚至被其他车辆遮挡的车道标记。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer vision-based multiple-lane detection on straight road and in a curve
A vision system was designed to detect multiple lanes on structured highway using an “estimate and detect” scheme. It detected the lane in which the vehicle was driving (the central lane) and estimated the possible position of two adjacent lanes. Then the detection was made based on these estimations. The vehicle was first recognized if it was driving on a straight road or in a curve using its GPS position and the OpenStreetMap digital map. The two cases were processed differently. For straight road, the central lane was detected in the original image using Hough transformation and a simplified perspective transformation was designed to make estimations. In the case of curve path, a complete perspective transformation was performed and the central lane was detected by scanning at each row in the top view image. The system was able to detected lane marks that were not distinct or even obstructed by other vehicles.
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