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Vehicle Classification and Counting for Vehicle Census

Vehicle classification has been significantly important to vehicle census as it provides traffic count information to reflect the traffic density of a particular roadway. However, it has been a time consuming and sophisticated task to classify different vehicles into the desired category. Beside...

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Main Authors: Chan, Dellas Su Chieng, Wang, Yin Chai
Format: Article
Language:English
Published: Universiti Teknikal Malaysia (UTEM) 2017
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/21885/1/Vehicle%20Classification.pdf
http://ir.unimas.my/id/eprint/21885/
http://journal.utem.edu.my/index.php/jtec/article/view/3178
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spelling my.unimas.ir.218852022-09-29T03:09:00Z http://ir.unimas.my/id/eprint/21885/ Vehicle Classification and Counting for Vehicle Census Chan, Dellas Su Chieng Wang, Yin Chai T Technology (General) Vehicle classification has been significantly important to vehicle census as it provides traffic count information to reflect the traffic density of a particular roadway. However, it has been a time consuming and sophisticated task to classify different vehicles into the desired category. Besides, the hardware-based technique used for classification leads to high cost of implementation and maintenance. Thus, we proposed an image processing based solution to extract the features of each vehicle in the traffic scene. The proposed framework incorporates a combination of detection, tracking and classification of vehicle to ensure high accuracy and performance for vehicle census. Experimental results show that our proposed framework can be applicable in real world applications. Universiti Teknikal Malaysia (UTEM) 2017 Article PeerReviewed text en http://ir.unimas.my/id/eprint/21885/1/Vehicle%20Classification.pdf Chan, Dellas Su Chieng and Wang, Yin Chai (2017) Vehicle Classification and Counting for Vehicle Census. Journal of Telecommunication, Electronic and Computer Engineering, 9 (3-11). ISSN 2289-8131 http://journal.utem.edu.my/index.php/jtec/article/view/3178
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Chan, Dellas Su Chieng
Wang, Yin Chai
Vehicle Classification and Counting for Vehicle Census
description Vehicle classification has been significantly important to vehicle census as it provides traffic count information to reflect the traffic density of a particular roadway. However, it has been a time consuming and sophisticated task to classify different vehicles into the desired category. Besides, the hardware-based technique used for classification leads to high cost of implementation and maintenance. Thus, we proposed an image processing based solution to extract the features of each vehicle in the traffic scene. The proposed framework incorporates a combination of detection, tracking and classification of vehicle to ensure high accuracy and performance for vehicle census. Experimental results show that our proposed framework can be applicable in real world applications.
format Article
author Chan, Dellas Su Chieng
Wang, Yin Chai
author_facet Chan, Dellas Su Chieng
Wang, Yin Chai
author_sort Chan, Dellas Su Chieng
title Vehicle Classification and Counting for Vehicle Census
title_short Vehicle Classification and Counting for Vehicle Census
title_full Vehicle Classification and Counting for Vehicle Census
title_fullStr Vehicle Classification and Counting for Vehicle Census
title_full_unstemmed Vehicle Classification and Counting for Vehicle Census
title_sort vehicle classification and counting for vehicle census
publisher Universiti Teknikal Malaysia (UTEM)
publishDate 2017
url http://ir.unimas.my/id/eprint/21885/1/Vehicle%20Classification.pdf
http://ir.unimas.my/id/eprint/21885/
http://journal.utem.edu.my/index.php/jtec/article/view/3178
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score 13.211869

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