TY - GEN
T1 - Real-Time lane detection and forward collision warning system based on stereo vision
AU - Song, Wenjie
AU - Fu, Mengyin
AU - Yang, Yi
AU - Wang, Meiling
AU - Wang, Xinyu
AU - Kornhauser, Alain
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/28
Y1 - 2017/7/28
N2 - This paper presents a real-Time and robust lane detection and forward collision warning technique based on stereo cameras. First, obstacles image is obtained through stereo matching and UV-disparity segmentation algorithm. Then, Inverse Perspective Mapping(IPM) and Sobel filtering are conducted to generate a low-noise top view of the road by fusing the obstacles image and the original image. Next, Hough Transformation for the top view map is completed and the extreme points(poles) are calculated as the detected lanes according to the traffic lanes model. Besides, the host lane is selected or supplemented among all the detected lanes and the nearest obstacle in this host lane is detected for the forward collision warning. Experimental results on the public data set indicate that our method can work effectively and real-Timely in the normal structured environment.
AB - This paper presents a real-Time and robust lane detection and forward collision warning technique based on stereo cameras. First, obstacles image is obtained through stereo matching and UV-disparity segmentation algorithm. Then, Inverse Perspective Mapping(IPM) and Sobel filtering are conducted to generate a low-noise top view of the road by fusing the obstacles image and the original image. Next, Hough Transformation for the top view map is completed and the extreme points(poles) are calculated as the detected lanes according to the traffic lanes model. Besides, the host lane is selected or supplemented among all the detected lanes and the nearest obstacle in this host lane is detected for the forward collision warning. Experimental results on the public data set indicate that our method can work effectively and real-Timely in the normal structured environment.
UR - http://www.scopus.com/inward/record.url?scp=85028038113&partnerID=8YFLogxK
U2 - 10.1109/IVS.2017.7995766
DO - 10.1109/IVS.2017.7995766
M3 - Conference contribution
AN - SCOPUS:85028038113
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 493
EP - 498
BT - IV 2017 - 28th IEEE Intelligent Vehicles Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th IEEE Intelligent Vehicles Symposium, IV 2017
Y2 - 11 June 2017 through 14 June 2017
ER -