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 there,...

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Bibliographic Details
Main Author:	Mohd Kiblee , Shahizul Eza
Format:	Thesis
Published:	2005
Subjects:	TL Motor vehicles. Aeronautics. Astronautics
Online Access:	http://eprints.uthm.edu.my/783/ http://eprints.uthm.edu.my/783/1/24_Pages_from_LANE_DETECTION_SYSTEM_FOR_AUTONOMOUS_VEHICLE_USING_IMAGE_PROCESSING_TECHNIQUES.pdf

id	uthm-783
recordtype	eprints
spelling	uthm-7832011-04-29T06:41:49Z Lane detection system for autonomous vehicle using image processing techniques Mohd Kiblee , Shahizul Eza TL Motor vehicles. Aeronautics. Astronautics 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 NonPeerReviewed application/pdf http://eprints.uthm.edu.my/783/1/24_Pages_from_LANE_DETECTION_SYSTEM_FOR_AUTONOMOUS_VEHICLE_USING_IMAGE_PROCESSING_TECHNIQUES.pdf Mohd Kiblee , Shahizul Eza (2005) Lane detection system for autonomous vehicle using image processing techniques. Masters thesis, Universiti Putra Malaysia. http://eprints.uthm.edu.my/783/
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Tun Hussein Onn Malaysia
building	UTHM Institutional Repository
collection	Online Access
topic	TL Motor vehicles. Aeronautics. Astronautics
spellingShingle	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
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
publishDate	2005
url	http://eprints.uthm.edu.my/783/ http://eprints.uthm.edu.my/783/1/24_Pages_from_LANE_DETECTION_SYSTEM_FOR_AUTONOMOUS_VEHICLE_USING_IMAGE_PROCESSING_TECHNIQUES.pdf
first_indexed	2018-09-05T10:44:47Z
last_indexed	2018-09-05T10:44:47Z
_version_	1610764032142213120

Lane detection system for autonomous vehicle using image processing techniques

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