Extraction of lane markings using orientation and vanishing point constraints in structured road scenes

Abstract

Extraction of lane markings is still a challenge due to the poor quality of lane markings and interferences from external circumstances. In this paper, we utilize line segments as low-level features to detect lane markings on structured road scenes. Our novel algorithm can be highlighted in four items as follows. Firstly, a road surface region is reasonably located using adaptive segmentation method, and then most of the interferences from the external circumstances are eliminated by Laplacian filter. Secondly, the line segments detected by the line segment detector are applied to represent the structural information of lanes. Thirdly, non-lane candidate markings are removed through orientation and vanishing point constraints. Finally, the lanes are accurately extracted from the remaining candidate lane marking. Experimental results on complex structured road scenarios in urban streets are shown and the effectiveness and robustness of our novel algorithm are underpinned by the experimental results.

Keywords:

• lane detection
• Laplacian filter
• line segment detector
• K-means clustering
• intelligent vehicle

2000 AMS Subject Classifications:

• 68T45
• 62H30
• 68U10

Acknowledgements

The authors thank the editors and the anonymous reviewers, whose comments helped to improve the paper greatly. This work was supported by the National Natural Science Foundation of China (No. 61172161), the Independent Research Funds of the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body (Hunan University, No. 71165002) and the Commonwealth of Australia under the Australia-China Science and Research Fund (ACSRF02541).