Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor

During the COVID-19 pandemic crisis in the middle 2021, the whole globe is shaken by the effect of the global pandemic. In order to reduce and combat the spread of the plague, many roadblock and inspection point had been placed in every entry point in every states. The implement of roadblock and ins...

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Main Author:	Mohd Sukor, Mohamad Saifullah
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Neural networks (Computer science)
Online Access:	https://ir.uitm.edu.my/id/eprint/95058/1/95058.pdf
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id	my-uitm-ir.95058
record_format	uketd_dc
spelling	my-uitm-ir.950582024-05-13T03:04:59Z Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor 2022 Mohd Sukor, Mohamad Saifullah Neural networks (Computer science) During the COVID-19 pandemic crisis in the middle 2021, the whole globe is shaken by the effect of the global pandemic. In order to reduce and combat the spread of the plague, many roadblock and inspection point had been placed in every entry point in every states. The implement of roadblock and inspection point is to control and know the amount of vehicles entering and exiting the states or district. The roadblock is attended by police officers who will inspect the vehicle passing thru. The drivers will require to have a permit in order to cross the states. The inspection will take a short duration between 1 to 2 minutes. If no problem arises, the vehicle can go thru the inspection point. In a busy day, the waiting line could reach to half an hour depending to which states or district. Therefore, it is convenient to implement an automatic detection system that can help recognise vehicle plate number. A model been proposed to help to recognize the Vehicle Plate Number. The proposed method consists of preprocessing and feature extraction stages. The vehicle plate number image will be resizing and convert into a grayscale image and converted again into binary image in the pre-processing step. The model will be developed by using Optical Character Recognition (OCR) classifier. To recognize it, the image of vehicle plate number will be used as a dataset. This system then will help the user to recognize vehicle plate number without manually inputted the data in. The highest success rates obtained from the system is 85.4%. 2022 Thesis https://ir.uitm.edu.my/id/eprint/95058/ https://ir.uitm.edu.my/id/eprint/95058/1/95058.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Fadzal, Ahmad Nazmi
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Fadzal, Ahmad Nazmi
topic	Neural networks (Computer science)
spellingShingle	Neural networks (Computer science) Mohd Sukor, Mohamad Saifullah Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor
description	During the COVID-19 pandemic crisis in the middle 2021, the whole globe is shaken by the effect of the global pandemic. In order to reduce and combat the spread of the plague, many roadblock and inspection point had been placed in every entry point in every states. The implement of roadblock and inspection point is to control and know the amount of vehicles entering and exiting the states or district. The roadblock is attended by police officers who will inspect the vehicle passing thru. The drivers will require to have a permit in order to cross the states. The inspection will take a short duration between 1 to 2 minutes. If no problem arises, the vehicle can go thru the inspection point. In a busy day, the waiting line could reach to half an hour depending to which states or district. Therefore, it is convenient to implement an automatic detection system that can help recognise vehicle plate number. A model been proposed to help to recognize the Vehicle Plate Number. The proposed method consists of preprocessing and feature extraction stages. The vehicle plate number image will be resizing and convert into a grayscale image and converted again into binary image in the pre-processing step. The model will be developed by using Optical Character Recognition (OCR) classifier. To recognize it, the image of vehicle plate number will be used as a dataset. This system then will help the user to recognize vehicle plate number without manually inputted the data in. The highest success rates obtained from the system is 85.4%.
format	Thesis
qualification_level	Bachelor degree
author	Mohd Sukor, Mohamad Saifullah
author_facet	Mohd Sukor, Mohamad Saifullah
author_sort	Mohd Sukor, Mohamad Saifullah
title	Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor
title_short	Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor
title_full	Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor
title_fullStr	Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor
title_full_unstemmed	Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor
title_sort	vehicle plate number recognition using optical character recognition(ocr) algorithm / mohamad saifullah mohd sukor
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/95058/1/95058.pdf
_version_	1804889945869910016

Vehicle plate number recognition using Optical Character Recognition(OCR) algorithm / Mohamad Saifullah Mohd Sukor

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