Paper
24 January 2011 Lane marking detection by extracting white regions with predefined width from bird's-eye road images
Sadayuki Abe, Kenji Shoji, Fubito Toyama, Juichi Miyamichi
Author Affiliations +
Proceedings Volume 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques; 78780T (2011) https://doi.org/10.1117/12.872312
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
Detecting lane markings on roads from in-vehicle camera images is very important because it is one of the fundamental tasks for autonomous running technology and safety driving support system. There are several lane markings detection methods using the width information, but most of these are considered to be insufficient for oblique markings. So, the primary intent of this paper is to propose a detecting lane markings method robust to orientation of markings. In this work, we focus on the width of lane markings standardized by road act in Japan, and propose a method for detecting white lane markings by extracting white regions with constant predefined width from bird's-eye road images after segmentation such as categorical color area one. The proposed method is based on the constrained Delaunay triangulation. The proposed method has a merit that can be measure an exact width for oblique markings on the bird's-eye images because it can be obtained perpendicular width for edge. The effectiveness of the proposed method was shown by experimental results for 187 actual road images taken from an in-vehicle camera.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sadayuki Abe, Kenji Shoji, Fubito Toyama, and Juichi Miyamichi "Lane marking detection by extracting white regions with predefined width from bird's-eye road images", Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 78780T (24 January 2011); https://doi.org/10.1117/12.872312
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Cited by 1 scholarly publication.
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KEYWORDS
Roads

Image segmentation

Cameras

Denoising

Safety

Imaging systems

Standards development

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