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Robust lane Extraction using Two-Dimension Declivity

Authors :
Mohamed Fakhfakh
Lotfi Chaari
Nizar Fakhfakh
Université de Sfax - University of Sfax
Navya
Traitement et Compréhension d’Images (IRIT-TCI)
Institut de recherche en informatique de Toulouse (IRIT)
Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées
Institut National Polytechnique (Toulouse) (Toulouse INP)
Centre National de la Recherche Scientifique - CNRS (FRANCE)
Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université Toulouse 1 Capitole - UT1 (FRANCE)
Navya (FRANCE)
Université de Sfax (TUNISIA)
Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France)
Source :
Artificial Intelligence and Soft Computing, 17th International Conference on Artificial Intelligence and Soft Computing (ICAISC), 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⟩, Artificial Intelligence and Soft Computing ISBN: 9783319912615, ICAISC (2)
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

National audience; 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.

Details

Language :
English
ISBN :
978-3-319-91261-5
ISBNs :
9783319912615
Database :
OpenAIRE
Journal :
Artificial Intelligence and Soft Computing, 17th International Conference on Artificial Intelligence and Soft Computing (ICAISC), 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⟩, Artificial Intelligence and Soft Computing ISBN: 9783319912615, ICAISC (2)
Accession number :
edsair.doi.dedup.....e2ae29ce6c271fa29ef9a60c944c92cd