计算机视觉道路估计与检测方法的比较研究

Hassan Facoiti, A. Boumezzough, S. Safi
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引用次数: 0

摘要

为了确保道路安全,自动驾驶是一个发展迅速的研究领域。最近,研究人员对道路的探测特别感兴趣。在过去的十年里,已经提出了几种新的方法。在本文中,我们提出了使用三种算法的道路检测方法的比较研究。一种是基于HOUGH变换,第二种是基于RANSAC算法,第三种是基于RADON变换。本文的目的是对这些方法进行比较,以便在计算机视觉中实现鲁棒估计方法,并将RADON方法应用于巷道的检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative study between computer vision methods for the estimation and detection of the roadway
Autonomous driving is a field of study that is progressing rapidly to ensure road safety. Recently, researchers have been particularly interested in the detection of the roadway. Several new approaches have been proposed in the last decade. In this paper, we present a comparative study of roadway detection methods using three algorithms. The one is based on HOUGH transform, the second on the RANSAC algorithm and the third on the RADON transform. The objective of this paper is to make a comparison of these method in order to robust estimation methods in computer vision and to apply the method of RADON for the detection of the roadway.
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