Rail extraction technique using gradient information and a priori shape model

This paper presents a comparative study of different rail detection techniques as well as a new method based on an efficient algorithm without any empirical thresholds. The main problem with rail detection is that both the track-bed and the exterior conditions (weather/light conditions) vary along the path. On the other hand, there are properties that can be exploited to improve the conventional lane detection. We present an edge detection based on the estimated position of the rails that follows the rail edges upwards in the image, determining a free-from-obstacles space. The existing techniques are also analyzed and compared.