Ekaterina Panfilova,1,2 Oleg S. Shipitko,3 Irina Kunina1,4
1Smart Engines Service LLC (Russian Federation) 2V. A. Trapeznikov Institute of Control Sciences of RAS (Russian Federation) 3Institute for Information Transmission Problems, RAS (Russian Federation) 4Institute for Information Transmission Problems (Russian Federation)
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The paper presents an algorithm for road markings detection in the image. The road markings are approximated by polyline with a restricted maximum curvature angle. To detect a marking segments an image is processed by a sliding window and for each window position, a straight line is detected by calculating Fast Hough Transform (FHT). Further, detected segments are grouped by relative position. Segments groups are then approximated by polylines. The algorithm was tested on real data collected from the front-looking camera of the autonomous vehicle driving at the experimental area “Kalibr” (Moscow). The road marking dataset used to evaluate the algorithm is publicly available at ftp://vis.iitp.ru/road markup dataset/. The precision of road markings detector was evaluated as 43%, and the recall as 73% which is sufficient for the autonomous vehicle precise positioning as demonstrated in [1].
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Ekaterina Panfilova, Oleg S. Shipitko, Irina Kunina, "Fast Hough transform-based road markings detection for autonomous vehicle," Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 116052B (4 January 2021); https://doi.org/10.1117/12.2587615