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Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi

ANPR system is used in automating access control and security such as identifying stolen cars in real time by installing it to police patrol cars, and detecting vehicles that are overspeeding on highways. However, this technology is still relatively expensive; in November 2014, the Royal Malaysian P...

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Main Authors: Abd Gani, Shamsul Fakhar, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Hamzah, Rostam Affendi, Azhar, Muhammad Aidil
Format: Article
Language:English
Published: Institute Of Advanced Engineering And Science (IAES) 2019
Subjects:
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utem.edu.my/id/eprint/24073/2/DEVELOPMENT%20OF%20PORTABLE%20AUTOMATIC%20NUMBER%20PLATE%20RECOGNITION%20%28ANPR%29%20SYSTEM%20ON%20RASPBERRY%20PI.pdf
http://eprints.utem.edu.my/id/eprint/24073/
http://ijece.iaescore.com/index.php/IJECE/article/view/17263/12352
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spelling my.utem.eprints.240732020-06-15T15:27:11Z http://eprints.utem.edu.my/id/eprint/24073/ Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi Abd Gani, Shamsul Fakhar Hamid, Mohd Saad Kadmin, Ahmad Fauzan Hamzah, Rostam Affendi Azhar, Muhammad Aidil T Technology (General) TK Electrical engineering. Electronics Nuclear engineering ANPR system is used in automating access control and security such as identifying stolen cars in real time by installing it to police patrol cars, and detecting vehicles that are overspeeding on highways. However, this technology is still relatively expensive; in November 2014, the Royal Malaysian Police (PDRM) purchased and installed 20 units of ANPR systems in their patrol vehicles costing nearly RM 30 million. In this paper a cheaper alternative of a portable ANPR system running on a Raspberry Pi with OpenCV library is presented. Once the camera captures an image, image desaturation, filtering, segmentation and character recognition is all done on the Raspberry Pi before the extracted number plate is displayed on the LCD and saved to a database. The main challenges in a portable application include crucial need of an efficient code and reduced computational complexity while offering improved flexibility. The performance time is also presented, where the whole process is run with a noticeable 3 seconds delay in getting the final output. Institute Of Advanced Engineering And Science (IAES) 2019-06 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24073/2/DEVELOPMENT%20OF%20PORTABLE%20AUTOMATIC%20NUMBER%20PLATE%20RECOGNITION%20%28ANPR%29%20SYSTEM%20ON%20RASPBERRY%20PI.pdf Abd Gani, Shamsul Fakhar and Hamid, Mohd Saad and Kadmin, Ahmad Fauzan and Hamzah, Rostam Affendi and Azhar, Muhammad Aidil (2019) Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi. International Journal Of Electrical And Computer Engineering (IJECE), 9 (3). pp. 1805-1813. ISSN 2088-8708 http://ijece.iaescore.com/index.php/IJECE/article/view/17263/12352 10.11591/ijece.v9i3.pp1805-1813
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Abd Gani, Shamsul Fakhar
Hamid, Mohd Saad
Kadmin, Ahmad Fauzan
Hamzah, Rostam Affendi
Azhar, Muhammad Aidil
Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi
description ANPR system is used in automating access control and security such as identifying stolen cars in real time by installing it to police patrol cars, and detecting vehicles that are overspeeding on highways. However, this technology is still relatively expensive; in November 2014, the Royal Malaysian Police (PDRM) purchased and installed 20 units of ANPR systems in their patrol vehicles costing nearly RM 30 million. In this paper a cheaper alternative of a portable ANPR system running on a Raspberry Pi with OpenCV library is presented. Once the camera captures an image, image desaturation, filtering, segmentation and character recognition is all done on the Raspberry Pi before the extracted number plate is displayed on the LCD and saved to a database. The main challenges in a portable application include crucial need of an efficient code and reduced computational complexity while offering improved flexibility. The performance time is also presented, where the whole process is run with a noticeable 3 seconds delay in getting the final output.
format Article
author Abd Gani, Shamsul Fakhar
Hamid, Mohd Saad
Kadmin, Ahmad Fauzan
Hamzah, Rostam Affendi
Azhar, Muhammad Aidil
author_facet Abd Gani, Shamsul Fakhar
Hamid, Mohd Saad
Kadmin, Ahmad Fauzan
Hamzah, Rostam Affendi
Azhar, Muhammad Aidil
author_sort Abd Gani, Shamsul Fakhar
title Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi
title_short Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi
title_full Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi
title_fullStr Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi
title_full_unstemmed Development Of Portable Automatic Number Plate Recognition (ANPR) System On Raspberry Pi
title_sort development of portable automatic number plate recognition (anpr) system on raspberry pi
publisher Institute Of Advanced Engineering And Science (IAES)
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24073/2/DEVELOPMENT%20OF%20PORTABLE%20AUTOMATIC%20NUMBER%20PLATE%20RECOGNITION%20%28ANPR%29%20SYSTEM%20ON%20RASPBERRY%20PI.pdf
http://eprints.utem.edu.my/id/eprint/24073/
http://ijece.iaescore.com/index.php/IJECE/article/view/17263/12352
_version_ 1671343085920976896
score 13.211869

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