A computer vision system for the classification of moving object

The aim of this research is to produce a system that can detect the moving object and classify it into three classes: “Humans, Vehicle and Animals”. Using fixed video camera in outdoors environment, the system will capture the images and digitize them using (Piccolo Pro II) frame grabber at a rate o...

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Bibliographic Details
Main Author:	Mohammed Osman Saleh Bilal, Sara
Format:	Thesis
Language:	English
Published:	2005
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/3000/1/SaraMohamedOsmanMFKE2005.pdf
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id	my-utm-ep.3000
record_format	uketd_dc
spelling	my-utm-ep.30002018-06-25T00:45:56Z A computer vision system for the classification of moving object 2005-04 Mohammed Osman Saleh Bilal, Sara TK Electrical engineering. Electronics Nuclear engineering The aim of this research is to produce a system that can detect the moving object and classify it into three classes: “Humans, Vehicle and Animals”. Using fixed video camera in outdoors environment, the system will capture the images and digitize them using (Piccolo Pro II) frame grabber at a rate of 25 frames per second. The Background Subtraction technique has been employed in the work as it is able to provide the most complete feature for data. However, it is extremely sensitive to dynamic changes like changing of illumination. Background Subtraction is done by taking the differenc e between any frame and the background in detecting the Moving Object. In order to reduce the effect of noise pixels resulting from the Background Subtraction operation, a number of pre-processing methods have been applied on the detected moving object. These preprocessing operations involve the use of median filter as well as morphological filters. Then the outline of the object will be extracted using border extraction technique. The classification makes use of both the shape and the dynamic features of the objects. In increasing the performance of the classification, all features are sequentially arranged so that the goal of this research is to be achieved. In this work, the performance achieved is 93% for class human, 93% for class vehicle and 64% for class animal. 2005-04 Thesis http://eprints.utm.my/id/eprint/3000/ http://eprints.utm.my/id/eprint/3000/1/SaraMohamedOsmanMFKE2005.pdf application/pdf en public 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 Mohammed Osman Saleh Bilal, Sara A computer vision system for the classification of moving object
description	The aim of this research is to produce a system that can detect the moving object and classify it into three classes: “Humans, Vehicle and Animals”. Using fixed video camera in outdoors environment, the system will capture the images and digitize them using (Piccolo Pro II) frame grabber at a rate of 25 frames per second. The Background Subtraction technique has been employed in the work as it is able to provide the most complete feature for data. However, it is extremely sensitive to dynamic changes like changing of illumination. Background Subtraction is done by taking the differenc e between any frame and the background in detecting the Moving Object. In order to reduce the effect of noise pixels resulting from the Background Subtraction operation, a number of pre-processing methods have been applied on the detected moving object. These preprocessing operations involve the use of median filter as well as morphological filters. Then the outline of the object will be extracted using border extraction technique. The classification makes use of both the shape and the dynamic features of the objects. In increasing the performance of the classification, all features are sequentially arranged so that the goal of this research is to be achieved. In this work, the performance achieved is 93% for class human, 93% for class vehicle and 64% for class animal.
format	Thesis
qualification_level	Master's degree
author	Mohammed Osman Saleh Bilal, Sara
author_facet	Mohammed Osman Saleh Bilal, Sara
author_sort	Mohammed Osman Saleh Bilal, Sara
title	A computer vision system for the classification of moving object
title_short	A computer vision system for the classification of moving object
title_full	A computer vision system for the classification of moving object
title_fullStr	A computer vision system for the classification of moving object
title_full_unstemmed	A computer vision system for the classification of moving object
title_sort	computer vision system for the classification of moving object
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2005
url	http://eprints.utm.my/id/eprint/3000/1/SaraMohamedOsmanMFKE2005.pdf
_version_	1747814434610348032

A computer vision system for the classification of moving object

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