Dynamic Programming
Road lane segmentation using dynamic programming for active safety vehicles
Pattern Recognition Letters
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Lane following and lane departure using a linear-parabolic model
Image and Vision Computing
Three-feature based automatic lane detection algorithm (TFALDA) for autonomous driving
IEEE Transactions on Intelligent Transportation Systems
Springrobot: a prototype autonomous vehicle and its algorithms for lane detection
IEEE Transactions on Intelligent Transportation Systems
Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation
IEEE Transactions on Intelligent Transportation Systems
Lane Detection With Moving Vehicles in the Traffic Scenes
IEEE Transactions on Intelligent Transportation Systems
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The following paper proposes a procedure for an automatic detection of road-lanes, which involves three main steps: two-category scene segmentation, a detection of lane segment candidates and decision making. The main contribution of the paper is an introduction of a new step - high-curvature edge filtering - into a typical road image processing. This step substantially reduces an amount of noise and yields an improved lane detection performance. The remaining two steps of lane detection are dynamic programming-based selection of line segments, and Hough transform-based selection of the most consistent segments. The proposed approach proved to produce good results for a variety of real-traffic conditions, including correct detection in heavily shadowed road images.