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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Main Author: Mohammed Osman Saleh Bilal, Sara
Format: Thesis
Language:English
Published: 2005
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Online Access:http://eprints.utm.my/id/eprint/3000/1/SaraMohamedOsmanMFKE2005.pdf
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spelling my.utm.30002018-06-25T00:45:56Z http://eprints.utm.my/id/eprint/3000/ A computer vision system for the classification of moving object 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 NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/3000/1/SaraMohamedOsmanMFKE2005.pdf Mohammed Osman Saleh Bilal, Sara (2005) A computer vision system for the classification of moving object. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
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
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
publishDate 2005
url http://eprints.utm.my/id/eprint/3000/1/SaraMohamedOsmanMFKE2005.pdf
http://eprints.utm.my/id/eprint/3000/
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score 13.211869