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On the design of a single lane-markings detectors regardless the on-board camera's position

In this article, we present an algorithm for lane marking features extraction and robust shape estimation of lane markings. The algorithm uses a new lane-marking features extractor followed by the robust fitting algorithm described by Tarel et. al. (2002) to estimate the lane-markings shape as a single analytical curve. The lane-marking features extractor is based on the fact that lane-markings widths are in a small range of possible values, on a road. This implies a geometric constrain on the observed lane-markings widths from a camera on-board a vehicle. The lane-marking features extractor uses this property to select pairs of edge points corresponding with a high probability to a section of lane-marking. This features extractor is especially designed to be robust to lighting conditions as shown by few experiments. The extracted features are then grouped to estimate the parameters of the analytical curve model of these lane-markings. With the proposed approach, the obtained detector is robust to different kinds of noise and perturbations, allowing us to use it with a camera in many positions. Finally, to illustrate this property, we briefly describe two applications of the proposed detector: accurate vehicle location on the road and estimation of the time to line crossing.