Lane Detection for Intelligent Vehicle under Different Illumination Conditions
Pingshu Ge, Lie Guo, Tao Zhang, Xiuchun Zhao, Jing Chang
Available Online June 2017.
- https://doi.org/10.2991/caai-17.2017.15How to use a DOI?
- intelligent vehicle; lane detection; linear lane model; Hough transform
- Lane detection is an important component for intelligent vehicle. A novel method for lane detection under complex illumination conditions is presented. An adaptive image segmentation technology based on OTSU algorithm was used to segment lane markings by combining the global and the local threshold. The improved Sobel operator was adapted to abstract the edges of the lane markings. The lane was finally identified using the improved Hough transform by limiting the range of lane parameters. On road experiments show that the proposed method has good accuracy and real-time performance under different illumination conditions.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Pingshu Ge AU - Lie Guo AU - Tao Zhang AU - Xiuchun Zhao AU - Jing Chang PY - 2017/06 DA - 2017/06 TI - Lane Detection for Intelligent Vehicle under Different Illumination Conditions BT - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017) PB - Atlantis Press SP - 77 EP - 80 SN - 1951-6851 UR - https://doi.org/10.2991/caai-17.2017.15 DO - https://doi.org/10.2991/caai-17.2017.15 ID - Ge2017/06 ER -