Research Article | OPEN ACCESS
Real Time Lane Detection in Autonomous Vehicles Using Image Processing
1Jasmine Wadhwa, 1G.S. Kalra and 2B.V. Kranthi
1School of Electronics Engineering, Lovely Professional University, Phagwara, Punjab, India
2Gitam University, Bangalore, India
Research Journal of Applied Sciences, Engineering and Technology 2015 4:429-433
Received: April ‎19, ‎2015 | Accepted: May ‎28, ‎2015 | Published: October 05, 2015
Abstract
The aim of this research is to detect and analyze the drivable path ahead of the autonomous vehicles by implementing path detection algorithms in MATLAB. This study presents a technique for real time detection of lanes marked on the road that can be used in autonomous vehicles. Since, for safe navigation of autonomous vehicles, detection of drivable path is a key requirement. Painted road markings on rural, urban roads and highways help to detect precisely the road area for the vehicle to move. Lane detection algorithms aim at finding the edges or boundaries of road within which vehicle can move. This target is accomplished by the use of camera set up on the vehicle that tracks road ahead of the vehicle. Lanes are detected through processing of each frame of video by edge detection and Hough transform techniques. This system can be further make compatible with the hardware of the vehicle to take certain actions depending on the detections made. This study presents potential approaches and requirements that are needed for detection of lanes, its algorithm and result.
Keywords:
Autonomous vehicles, boundaries, lane detection, masking,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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