A Framework for the Development of Robust Lane Recognition Systems

Video-based navigation systems can provide more realistic navigation information to drivers by guiding their directions on a live video. To make video-based navigation systems, a robust lane recognition system is essential for 1) various road conditions such as damaged road and occluded road markings due to cars on the road, and 2) poor illumination conditions such as backlight, sunset, and so on. In this paper, a framework to make a robust lane recognition system is presented, which can overcome the difficulties mentioned above. In the proposed framework, a priori knowledge of the shape of road markings is exploited to reduce false positives and color information of lane markings are carefully analyzed to remove the poor illumination conditions. Based on the idea that the illumination effects to the background region, i.e., a set of pixels in the road region without lane markings, can be used to eliminate the illumination effects to lane markings, the proposed approach is designed to distinguish yellow lane markings from white lane markings. Experimental results are provided to show the effectiveness of the proposed lane recognition system for a various road and illumination conditions.