Title :
Vision based lane detection in autonomous vehicle
Author :
Shu, Yuan ; Tan, Zheng
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., China
Abstract :
A novel method for finding and tracking road lanes for vision-guided autonomous vehicle navigation is present in this paper. First an inverse perspective mapping is applied in order to remove the perspective from the camera observed image. Then the edges of the road lanes are detected from the inverse perspective mapping images. A particle filtering algorithm is used which allows us to compute the likelihood between all the particles with the edge images, then the three parameters of the real state of lanes can be estimated. The new lane detection method described in this paper has been tested in real road images and the result is robust and reliable.
Keywords :
computer vision; computerised navigation; edge detection; road vehicles; traffic engineering computing; autonomous vehicle navigation; edge images; inverse perspective mapping; particle filtering; road lanes; vision based lane detection; Cameras; Filtering algorithms; Image edge detection; Mobile robots; Navigation; Remotely operated vehicles; Road vehicles; State estimation; Testing; Vehicle detection;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343725
