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An improved lane boundaries detection based on dynamic ROI

机译:基于动态ROI的改进车道边界检测

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In modern society, with the economic conditions getting better, more and more vehicles are produced. So many vehicles bring about the rapid development of traffic transportation and the traffic accidents happen frequently. With the fast development of computer technology, more and more interests are focused on vision navigation technology in Intelligent Vehicle System. At the same time, lane detection is an important component of intelligent vehicle vision navigation system. In order to improve the real-time detection, an improved lane boundaries detection based on dynamic regions of interest is presented. The approach is an essential tasking both autonomous lane vehicles research and active safety system development. Lane detection is, however, still a challenging issue due to the complexity of the real road scenes. Our approach takes advantage of the image preprocessing with different processing on the images with different illumination, ROI decision algorithm and lane detection based on the vanishing point and Hough transform. The achieved results reveal that the Hough transform with the dynamic ROI algorithm and vanishing point method is more effective.
机译:在现代社会中,随着经济状况的改善,越来越多的汽车被生产出来。如此众多的车辆带动了交通运输的飞速发展,交通事故频发。随着计算机技术的飞速发展,智能车辆系统中的视觉导航技术越来越受到关注。同时,车道检测是智能车辆视觉导航系统的重要组成部分。为了改进实时检测,提出了一种基于感兴趣的动态区域的改进的车道边界检测。该方法对自动驾驶车辆研究和主动安全系统开发都是必不可少的任务。然而,由于实际道路场景的复杂性,车道检测仍然是一个具有挑战性的问题。我们的方法利用了对图像进行预处理,对不同光照度的图像进行不同处理,ROI决策算法以及基于消失点和霍夫变换的车道检测的优势。所得结果表明,采用动态ROI算法和消失点方法进行的Hough变换更为有效。

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