Road Lane Detection with Elimination of High-Curvature Edges
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
A real-time versatile roadway path extraction and tracking on an FPGA platform
Computer Vision and Image Understanding
A situation-adaptive lane-keeping support system: overview of the SAFELANE approach
IEEE Transactions on Intelligent Transportation Systems
Crossing road monitoring system based on adaptive decision for illegal situation
Applied Soft Computing
A comparative study of vision-based lane detection methods
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
A lane detection and tracking method for driver assistance system
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
A novel system for robust lane detection and tracking
Signal Processing
MARVEL: multiple antenna based relative vehicle localizer
Proceedings of the 18th annual international conference on Mobile computing and networking
Keeping the vehicle on the road: A survey on on-road lane detection systems
ACM Computing Surveys (CSUR)
Recent progress in road and lane detection: a survey
Machine Vision and Applications
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A lane-detection method aimed at handling moving vehicles in the traffic scenes is proposed in this brief. First, lane marks are extracted based on color information. The extraction of lane-mark colors is designed in a way that is not affected by illumination changes and the proportion of space that vehicles on the road occupy. Next, for vehicles that have the same colors as the lane marks, we utilize size, shape, and motion information to distinguish them from the real lane marks. The mechanism effectively eliminates the influence of passing vehicles when performing lane detection. Finally, pixels in the extracted lane-mark mask are accumulated to find the boundary lines of the lane. The proposed algorithm is able to robustly find the left and right boundary lines of the lane and is not affected by the passing traffic. Experimental results show that the proposed method works well on marked roads in various lighting conditions