Title :
Vision-based lane detection for an autonomous ground vehicle: A comparative field test
Author :
Bush, Forrest N. ; Esposito, Joel M.
Author_Institution :
US Naval Acad., Annapolis, MD, USA
Abstract :
We examine the problem of designing computer vision algorithms to autonomously drive an off road vehicle between two lane markings painted on the ground. In this paper we describe field tests used to compare the efficacy of two popular line extractions techniques from the literature: the Hough Transform and the RANSAC Algorithm. Although it is very implementation dependent, we found the Hough Transform to be superior to the RANSAC algorithm in both speed and accuracy for identifying lane markings in the off road environment.
Keywords :
Hough transforms; image sensors; mobile robots; remotely operated vehicles; robot vision; Hough transform; RANSAC algorithm; autonomous ground vehicle; comparative field test; computer vision algorithms design; line extractions techniques; off road vehicle; vision-based lane detection; Computer vision; Global Positioning System; Intelligent vehicles; Land vehicles; Mobile robots; Remotely operated vehicles; Road transportation; Road vehicles; Testing; Vehicle detection; Unmanned Vehicles; Vision-Based Control;
Conference_Titel :
System Theory (SSST), 2010 42nd Southeastern Symposium on
Conference_Location :
Tyler, TX
Print_ISBN :
978-1-4244-5690-1
DOI :
10.1109/SSST.2010.5442799
