Moving object detection in a sequence of images taken from non-stationary camera

Moving object detection is a vital aspect of motion analysis. It has drawn an increasing attention in the recent years due to its applications such as in communication, traffic monitoring, security surveillance, robot navigation and servoing. Despite the fact that much research efforts have be...

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Main Author:	Cholan, Noran Azizan
Format:	Thesis
Language:	English
Published:	2004
Subjects:	TK Electrical engineering Electronics Nuclear engineering TK7800-8360 Electronics
Online Access:	http://eprints.uthm.edu.my/7707/1/24p%20NORAN%20AZIZAN%20CHOLAN.pdf
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id	my-uthm-ep.7707
record_format	uketd_dc
spelling	my-uthm-ep.77072022-09-19T02:09:16Z Moving object detection in a sequence of images taken from non-stationary camera 2004-09 Cholan, Noran Azizan TK Electrical engineering. Electronics Nuclear engineering TK7800-8360 Electronics Moving object detection is a vital aspect of motion analysis. It has drawn an increasing attention in the recent years due to its applications such as in communication, traffic monitoring, security surveillance, robot navigation and servoing. Despite the fact that much research efforts have been devoted to this area, detecting moving object using non-stationary moving camera remains a great challenge. The research undertaken in this thesis is mainly concentrated on developing a reliable and robust detection system which incorporates some operation on images such as thresholding, blob labelling, blob matching, filtering and blob analysis. The basic idea behind this system is that the motion of the moving object is di fferent with the motion of background object. Path transversed within a certain period of observation of the moving object is usually longer than background object. By using blob labelling and blob matching operation, this system would be able to track binary blobs over an arbitarily long image sequence. The criteria for matching binary blobs from two adjacent frames are position, height, width, area, colour and aspect ratio. If the the path transversed ofa binary blob within a certain period of observation is sufficiently long, then the tracked blob is considered as moving object. 2004-09 Thesis http://eprints.uthm.edu.my/7707/ http://eprints.uthm.edu.my/7707/1/24p%20NORAN%20AZIZAN%20CHOLAN.pdf text en public mphil masters Universiti Teknologi Malaysia Fakulti Kejuruteraan Elektrik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering TK7800-8360 Electronics
spellingShingle	TK Electrical engineering Electronics Nuclear engineering TK7800-8360 Electronics Cholan, Noran Azizan Moving object detection in a sequence of images taken from non-stationary camera
description	Moving object detection is a vital aspect of motion analysis. It has drawn an increasing attention in the recent years due to its applications such as in communication, traffic monitoring, security surveillance, robot navigation and servoing. Despite the fact that much research efforts have been devoted to this area, detecting moving object using non-stationary moving camera remains a great challenge. The research undertaken in this thesis is mainly concentrated on developing a reliable and robust detection system which incorporates some operation on images such as thresholding, blob labelling, blob matching, filtering and blob analysis. The basic idea behind this system is that the motion of the moving object is di fferent with the motion of background object. Path transversed within a certain period of observation of the moving object is usually longer than background object. By using blob labelling and blob matching operation, this system would be able to track binary blobs over an arbitarily long image sequence. The criteria for matching binary blobs from two adjacent frames are position, height, width, area, colour and aspect ratio. If the the path transversed ofa binary blob within a certain period of observation is sufficiently long, then the tracked blob is considered as moving object.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Cholan, Noran Azizan
author_facet	Cholan, Noran Azizan
author_sort	Cholan, Noran Azizan
title	Moving object detection in a sequence of images taken from non-stationary camera
title_short	Moving object detection in a sequence of images taken from non-stationary camera
title_full	Moving object detection in a sequence of images taken from non-stationary camera
title_fullStr	Moving object detection in a sequence of images taken from non-stationary camera
title_full_unstemmed	Moving object detection in a sequence of images taken from non-stationary camera
title_sort	moving object detection in a sequence of images taken from non-stationary camera
granting_institution	Universiti Teknologi Malaysia
granting_department	Fakulti Kejuruteraan Elektrik
publishDate	2004
url	http://eprints.uthm.edu.my/7707/1/24p%20NORAN%20AZIZAN%20CHOLAN.pdf
_version_	1747831184403988480

Moving object detection in a sequence of images taken from non-stationary camera

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