Lane detection for intelligent vehicles in challenging scenarios
2nd International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2010, Liverpool, İngiltere, 28 - 30 Temmuz 2010, ss.37-43, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/cicsyn.2010.60
- Basıldığı Şehir: Liverpool
- Basıldığı Ülke: İngiltere
- Sayfa Sayıları: ss.37-43
- Anahtar Kelimeler: Computer vision, Hyperbola-pairs, Intelligent vehicles, Lane detection, RANSAC
- Boğaziçi Üniversitesi Adresli: Evet
Özet
Various image processing techniques and geometric models have been applied in vision based lane detection subsystems of intelligent vehicles and Advanced Driver Assistance Systems (ADAS). However, challenging conditions such as strong shadows, occlusions, eroded markings, high curvatures are ongoing issues in this topic. In this paper, a novel lane extraction method based on symmetrical local threshold is proposed with the hyperbola road model. Optimal model fit of lane distribution and hyperbola-pairs are estimated with RANdom SAmple Consensus (RANSAC) technique. The system computes the road geometry, vehicle position and direction both on urban road and country roads. Results have been presented on images with strong shadows, high curvature and eroded markings. Road and vehicle parameters computed on synthetic images are compared with ground truth information to show the accuracy of the proposed method. © 2010 IEEE.