Performance evaluation of automatic number plate recognition on android smartphone platform

Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. Previous researches implemented ANPR system on personal computer (PC) with high resolution camera and high computational capability. On the other hand, not...

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Main Authors: Gunawan, Teddy Surya, Mutholib, Abdul, Kartiwi, Mira
Format: Article
Language:English
English
Published: Institute of Advanced Engineering and Science 2017
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Online Access:http://irep.iium.edu.my/57754/1/GunawanANPRdevelopment_7736-8390-1-Published.pdf
http://irep.iium.edu.my/57754/7/Performance%20evaluation%20of%20automatic%20number%20plate%20recognition%20on%20android%20smartphone%20platform.pdf
http://irep.iium.edu.my/57754/
http://www.iaescore.com/journals/index.php/IJECE/article/view/7736
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spelling my.iium.irep.577542018-01-19T02:14:17Z http://irep.iium.edu.my/57754/ Performance evaluation of automatic number plate recognition on android smartphone platform Gunawan, Teddy Surya Mutholib, Abdul Kartiwi, Mira TK Electrical engineering. Electronics Nuclear engineering Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. Previous researches implemented ANPR system on personal computer (PC) with high resolution camera and high computational capability. On the other hand, not many researches have been conducted on the design and implementation of ANPR in smartphone platforms which has limited camera resolution and processing speed. In this paper, various steps to optimize ANPR, including pre-processing, segmentation, and optical character recognition (OCR) using artificial neural network (ANN) and template matching, were described. The proposed ANPR algorithm was based on Tesseract and Leptonica libraries. For comparison purpose, the template matching based OCR will be compared to ANN based OCR. Performance of the proposed algorithm was evaluated on the developed Malaysian number plates’ image database captured by smartphone’s camera. Results showed that the accuracy and processing time of the proposed algorithm using template matching was 97.5% and 1.13 seconds, respectively. On the other hand, the traditional algorithm using template matching only obtained 83.7% recognition rate with 0.98 second processing time. It shows that our proposed ANPR algorithm improved the recognition rate with negligible additional processing time. Institute of Advanced Engineering and Science 2017-08 Article REM application/pdf en http://irep.iium.edu.my/57754/1/GunawanANPRdevelopment_7736-8390-1-Published.pdf application/pdf en http://irep.iium.edu.my/57754/7/Performance%20evaluation%20of%20automatic%20number%20plate%20recognition%20on%20android%20smartphone%20platform.pdf Gunawan, Teddy Surya and Mutholib, Abdul and Kartiwi, Mira (2017) Performance evaluation of automatic number plate recognition on android smartphone platform. International Journal of Electrical and Computer Engineering, 7 (3). pp. 1941-1951. ISSN 2088-8708 http://www.iaescore.com/journals/index.php/IJECE/article/view/7736 10.11591/ijece.v7i3.pp1941-1951
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Gunawan, Teddy Surya
Mutholib, Abdul
Kartiwi, Mira
Performance evaluation of automatic number plate recognition on android smartphone platform
description Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. Previous researches implemented ANPR system on personal computer (PC) with high resolution camera and high computational capability. On the other hand, not many researches have been conducted on the design and implementation of ANPR in smartphone platforms which has limited camera resolution and processing speed. In this paper, various steps to optimize ANPR, including pre-processing, segmentation, and optical character recognition (OCR) using artificial neural network (ANN) and template matching, were described. The proposed ANPR algorithm was based on Tesseract and Leptonica libraries. For comparison purpose, the template matching based OCR will be compared to ANN based OCR. Performance of the proposed algorithm was evaluated on the developed Malaysian number plates’ image database captured by smartphone’s camera. Results showed that the accuracy and processing time of the proposed algorithm using template matching was 97.5% and 1.13 seconds, respectively. On the other hand, the traditional algorithm using template matching only obtained 83.7% recognition rate with 0.98 second processing time. It shows that our proposed ANPR algorithm improved the recognition rate with negligible additional processing time.
format Article
author Gunawan, Teddy Surya
Mutholib, Abdul
Kartiwi, Mira
author_facet Gunawan, Teddy Surya
Mutholib, Abdul
Kartiwi, Mira
author_sort Gunawan, Teddy Surya
title Performance evaluation of automatic number plate recognition on android smartphone platform
title_short Performance evaluation of automatic number plate recognition on android smartphone platform
title_full Performance evaluation of automatic number plate recognition on android smartphone platform
title_fullStr Performance evaluation of automatic number plate recognition on android smartphone platform
title_full_unstemmed Performance evaluation of automatic number plate recognition on android smartphone platform
title_sort performance evaluation of automatic number plate recognition on android smartphone platform
publisher Institute of Advanced Engineering and Science
publishDate 2017
url http://irep.iium.edu.my/57754/1/GunawanANPRdevelopment_7736-8390-1-Published.pdf
http://irep.iium.edu.my/57754/7/Performance%20evaluation%20of%20automatic%20number%20plate%20recognition%20on%20android%20smartphone%20platform.pdf
http://irep.iium.edu.my/57754/
http://www.iaescore.com/journals/index.php/IJECE/article/view/7736
_version_ 1643615212328189952
score 13.209306