Fast Hough transform-based road markings detection for autonomous vehicle

Ekaterina Panfilova; Oleg S. Shipitko; Irina Kunina

doi:10.1117/12.2587615

4 January 2021 Fast Hough transform-based road markings detection for autonomous vehicle

Ekaterina Panfilova, Oleg S. Shipitko, Irina Kunina

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 116052B (2021) https://doi.org/10.1117/12.2587615
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

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].

Citation Download Citation

Ekaterina Panfilova, Oleg S. Shipitko, and 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

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