Robust lane Extraction using Two-Dimension Declivity

Mohamed Fakhfakh (1, 2) , Nizar Fakhfakh (2) , Lotfi Chaari (3, 1, 4)

1 Université de Sfax - University of Sfax
2 Navya
3 IRIT-TCI - Traitement et Compréhension d’Images
4 Toulouse INP - Institut National Polytechnique (Toulouse)

A new robust lane marking extraction algorithm for monocular vision is proposed based on Two-Dimension Declivity. It is designed for the urban roads with difficult conditions (shadow, high brightness, etc.). In this paper, we propose a locating system which, from an embedded camera, allows lateral positioning of a vehicle by detecting road markings. The primary contribution of the paper is that it supplies a robust method made up of six steps: (i) Image Pre-processing, (ii) Enhanced Declivity Operator (DE), (iii) Mathematical Morphology, (iv) Labeling, (v) Hough Transform and (vi) Line Segment Clustering. The experimental results have shown the high performance of our algorithm in various road scenes. This validation stage has been done with a sequence of simulated images. Results are very promising: more than 90% of marking lines are extracted for less than 12% of false alarm.

Mots clés: Curve lane detection; Declivity operator; Road marking; Clustering; Hough transform

Domaines: Algorithme et structure de données [cs.DS]

Mohamed Fakhfakh, Nizar Fakhfakh, Lotfi Chaari. Robust lane Extraction using Two-Dimension Declivity. 17th International Conference on Artificial Intelligence and Soft Computing (ICAISC), Jun 2018, Zakopane, Poland. pp.14-24, ⟨10.1007/978-3-319-91262-2_2⟩. ⟨hal-02938620⟩