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Erschienen in:
Moving Object Detection and Tracking Based on Three-Frame Difference and Background Subtraction with Laplace Filter Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Robust Lane Extraction Using Two-Dimension Declivity

verfasst von : Mohamed Fakhfakh, Nizar Fakhfakh, Lotfi Chaari

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

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.

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Vorheriges Kapitel Moving Object Detection and Tracking Based on Three-Frame Difference and Background Subtraction with Laplace Filter
Nächstes Kapitel Segmentation of the Proximal Femur by the Analysis of X-ray Imaging Using Statistical Models of Shape and Appearance
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Metadaten
Titel
Robust Lane Extraction Using Two-Dimension Declivity
verfasst von
Mohamed Fakhfakh
Nizar Fakhfakh
Lotfi Chaari
Copyright-Jahr
2018
Buch
Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-91261-5

Electronic ISBN: 978-3-319-91262-2

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-91262-2_2