Multiple vehicle detection and segmentation

Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. Previously, this burdensome task was performed by human operator in traffic monitoring centre. Nevertheless, the increasing number of vehicl...

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Bibliographic Details
Main Author:	Hasan, Ahmad Fariz
Format:	Thesis
Language:	English
Published:	2012
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/32314/5/AhmadFarizHasanMFKE2012.pdf
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id	my-utm-ep.32314
record_format	uketd_dc
spelling	my-utm-ep.323142018-05-27T07:44:15Z Multiple vehicle detection and segmentation 2012-01 Hasan, Ahmad Fariz TK Electrical engineering. Electronics Nuclear engineering Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. Previously, this burdensome task was performed by human operator in traffic monitoring centre. Nevertheless, the increasing number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. The research undertaken in this thesis is mainly concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The proposed system is able to automatically segment vehicle extracted from heavy traffic scene. In this work, optical flow estimation alongside with blob analysis technique is proposed in order to detect the moving vehicle. Since there is no reference background on the image, optical flow technique is used to distinguish between background from video scene with moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene. 2012-01 Thesis http://eprints.utm.my/id/eprint/32314/ http://eprints.utm.my/id/eprint/32314/5/AhmadFarizHasanMFKE2012.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:72739?site_name=Restricted Repository masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Hasan, Ahmad Fariz Multiple vehicle detection and segmentation
description	Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. Previously, this burdensome task was performed by human operator in traffic monitoring centre. Nevertheless, the increasing number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. The research undertaken in this thesis is mainly concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The proposed system is able to automatically segment vehicle extracted from heavy traffic scene. In this work, optical flow estimation alongside with blob analysis technique is proposed in order to detect the moving vehicle. Since there is no reference background on the image, optical flow technique is used to distinguish between background from video scene with moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.
format	Thesis
qualification_level	Master's degree
author	Hasan, Ahmad Fariz
author_facet	Hasan, Ahmad Fariz
author_sort	Hasan, Ahmad Fariz
title	Multiple vehicle detection and segmentation
title_short	Multiple vehicle detection and segmentation
title_full	Multiple vehicle detection and segmentation
title_fullStr	Multiple vehicle detection and segmentation
title_full_unstemmed	Multiple vehicle detection and segmentation
title_sort	multiple vehicle detection and segmentation
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2012
url	http://eprints.utm.my/id/eprint/32314/5/AhmadFarizHasanMFKE2012.pdf
_version_	1747815972773822464

Multiple vehicle detection and segmentation

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