Abstract
Vision-based lane detection is a critical issue in the field of intelligent transportation and safety driving, and is useful to predict the position of the car on the road. By analyzing many images in database and experimental results, we find that brightness difference between lane marking and road is the stable feature in various challenging scenarios. So in this paper, we propose a new, fast and effective lane detection approach based on the brightness difference. We apply the brightness difference feature in “Verify” phase in order to reduce computation and filter the wrong lines. Experimental results show that the proposed method could perform well in real-time application, and it is robust against cracks on the roads, the curved lanes.
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