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Robust lane Extraction using Two-Dimension Declivity
- 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.
- Subjects :
- Road marking
Computer science
Algorithme et structure de données
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]
02 engineering and technology
Mathematical morphology
Clustering
Hough transform
law.invention
Line segment
Dimension (vector space)
law
Declivity operator
0502 economics and business
Shadow
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Cluster analysis
050210 logistics & transportation
business.industry
Curve lane detection
05 social sciences
020206 networking & telecommunications
Artificial intelligence
False alarm
business
Monocular vision
Subjects
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