Lane detection system for autonomous vehicle using image processing techniques

A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. This would mean, to go to a specific destination, a driver will just has to key in the desired destination and the system will be enabled automatically by the computer. From...

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Main Author:	Mohd Kiblee, Shahizul Eza
Format:	Thesis
Language:	English
Published:	2005
Subjects:	TL Motor vehicles Aeronautics Astronautics
Online Access:	http://eprints.uthm.edu.my/7968/1/24p%20SHAHIZUL%20EZA%20MOHD%20KIBLEE.pdf
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id	my-uthm-ep.7968
record_format	uketd_dc
spelling	my-uthm-ep.79682022-11-02T06:51:03Z Lane detection system for autonomous vehicle using image processing techniques 2005-11 Mohd Kiblee, Shahizul Eza TL Motor vehicles. Aeronautics. Astronautics TL1-484 Motor vehicles. Cycles A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. This would mean, to go to a specific destination, a driver will just has to key in the desired destination and the system will be enabled automatically by the computer. From there, the car would take over and drive to destination with no human input. The car would be able to sense its environment and change maneuver and speed when necessary. A system for road marking detection has been set up during the course of this master's thesis project. In the development of the software, images acquired from a front looking video camera mounted inside the vehicle were used. The problem of using computer vision to develop lane detection system for autonomous vehicle is road marking characteristic. Since the strongest characteristic of a road marking image are the edges, the road marking detection step is based on edge detection. For the detection of the straight edge lines, a Radon based method was chosen. Due to peak spreading in Radon space, the difficulty of detecting the correct peak in Radon space was encountered. A Radon peak detection algorithm was developed based on two values, Rand O. These values make the system robust to the different types of road marking such as continuous road marking, discontinuous road marking and road with shadow. The performance of the road marking detection algorithm was investigated over several different short image sequences. The different sequences included normal countly road driving, a number of different road marking configurations, such as continuous, intermittent and combinations of and images with shadows. The system performs well during the experiments within the difference road condition state above. The work done in this thesis can be used as a starting point in the development of for example a lane departure warning system. The potential of such a system is further increased by merging information retrieved from images with information from the vehicle such as vehicle speed, steering angle and acceleration. 2005-11 Thesis http://eprints.uthm.edu.my/7968/ http://eprints.uthm.edu.my/7968/1/24p%20SHAHIZUL%20EZA%20MOHD%20KIBLEE.pdf text en public mphil masters Universiti Putra Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English
topic	TL Motor vehicles Aeronautics Astronautics TL Motor vehicles Aeronautics Astronautics
spellingShingle	TL Motor vehicles Aeronautics Astronautics TL Motor vehicles Aeronautics Astronautics Mohd Kiblee, Shahizul Eza Lane detection system for autonomous vehicle using image processing techniques
description	A completely autonomous vehicle is one in which a computer performs all the tasks that the human driver normally would. This would mean, to go to a specific destination, a driver will just has to key in the desired destination and the system will be enabled automatically by the computer. From there, the car would take over and drive to destination with no human input. The car would be able to sense its environment and change maneuver and speed when necessary. A system for road marking detection has been set up during the course of this master's thesis project. In the development of the software, images acquired from a front looking video camera mounted inside the vehicle were used. The problem of using computer vision to develop lane detection system for autonomous vehicle is road marking characteristic. Since the strongest characteristic of a road marking image are the edges, the road marking detection step is based on edge detection. For the detection of the straight edge lines, a Radon based method was chosen. Due to peak spreading in Radon space, the difficulty of detecting the correct peak in Radon space was encountered. A Radon peak detection algorithm was developed based on two values, Rand O. These values make the system robust to the different types of road marking such as continuous road marking, discontinuous road marking and road with shadow. The performance of the road marking detection algorithm was investigated over several different short image sequences. The different sequences included normal countly road driving, a number of different road marking configurations, such as continuous, intermittent and combinations of and images with shadows. The system performs well during the experiments within the difference road condition state above. The work done in this thesis can be used as a starting point in the development of for example a lane departure warning system. The potential of such a system is further increased by merging information retrieved from images with information from the vehicle such as vehicle speed, steering angle and acceleration.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohd Kiblee, Shahizul Eza
author_facet	Mohd Kiblee, Shahizul Eza
author_sort	Mohd Kiblee, Shahizul Eza
title	Lane detection system for autonomous vehicle using image processing techniques
title_short	Lane detection system for autonomous vehicle using image processing techniques
title_full	Lane detection system for autonomous vehicle using image processing techniques
title_fullStr	Lane detection system for autonomous vehicle using image processing techniques
title_full_unstemmed	Lane detection system for autonomous vehicle using image processing techniques
title_sort	lane detection system for autonomous vehicle using image processing techniques
granting_institution	Universiti Putra Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2005
url	http://eprints.uthm.edu.my/7968/1/24p%20SHAHIZUL%20EZA%20MOHD%20KIBLEE.pdf
_version_	1776103278173487104

Lane detection system for autonomous vehicle using image processing techniques

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