Malaysian license plate number extraction using character segmentation / Zainab Zakaria

Car License Plate Recognition (CLPR) method is a key too many traffic oriented applications such as traffic monitoring, border monitoring and in toll areas. Car License Plate Recognition (CLPR) consists of three phases: license plate detection, character segmentation and character recognition. Ja...

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Main Author: Zakaria, Zainab
Format: Thesis
Language:English
Published: 2007
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/1014/2/TB_ZAINAB%20ZAKARIA%20CS%2007_5%20P01.pdf
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spelling my-uitm-ir.10142018-10-19T07:47:59Z Malaysian license plate number extraction using character segmentation / Zainab Zakaria 2007 Zakaria, Zainab Electronic Computers. Computer Science Car License Plate Recognition (CLPR) method is a key too many traffic oriented applications such as traffic monitoring, border monitoring and in toll areas. Car License Plate Recognition (CLPR) consists of three phases: license plate detection, character segmentation and character recognition. Jabatan Pengangkutan Jalan (JPJ) has a problem to detect a non-standardized Malaysian license plate number. This project proposes to extract static image of "PUTRAJAYA" Malaysian license plate number using character segmentation. The segmentation process will divided into vertical segmentation and horizontal segmentation. This application will produce the individual character. Character segmentation is an important step in Car License Plate Recognition (CLPR). There are many dif-faculties in this step, such as the influence of image noise, plate frame, rivet, the space mark and so on. Faculty of Computer and Mathematical Sciences 2007 Thesis https://ir.uitm.edu.my/id/eprint/1014/ https://ir.uitm.edu.my/id/eprint/1014/2/TB_ZAINAB%20ZAKARIA%20CS%2007_5%20P01.pdf text en public degree Universiti Teknologi MARA Faculty of Information Technology and Quantitative Sciences
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
topic Electronic Computers
Computer Science
spellingShingle Electronic Computers
Computer Science
Zakaria, Zainab
Malaysian license plate number extraction using character segmentation / Zainab Zakaria
description Car License Plate Recognition (CLPR) method is a key too many traffic oriented applications such as traffic monitoring, border monitoring and in toll areas. Car License Plate Recognition (CLPR) consists of three phases: license plate detection, character segmentation and character recognition. Jabatan Pengangkutan Jalan (JPJ) has a problem to detect a non-standardized Malaysian license plate number. This project proposes to extract static image of "PUTRAJAYA" Malaysian license plate number using character segmentation. The segmentation process will divided into vertical segmentation and horizontal segmentation. This application will produce the individual character. Character segmentation is an important step in Car License Plate Recognition (CLPR). There are many dif-faculties in this step, such as the influence of image noise, plate frame, rivet, the space mark and so on.
format Thesis
qualification_level Bachelor degree
author Zakaria, Zainab
author_facet Zakaria, Zainab
author_sort Zakaria, Zainab
title Malaysian license plate number extraction using character segmentation / Zainab Zakaria
title_short Malaysian license plate number extraction using character segmentation / Zainab Zakaria
title_full Malaysian license plate number extraction using character segmentation / Zainab Zakaria
title_fullStr Malaysian license plate number extraction using character segmentation / Zainab Zakaria
title_full_unstemmed Malaysian license plate number extraction using character segmentation / Zainab Zakaria
title_sort malaysian license plate number extraction using character segmentation / zainab zakaria
granting_institution Universiti Teknologi MARA
granting_department Faculty of Information Technology and Quantitative Sciences
publishDate 2007
url https://ir.uitm.edu.my/id/eprint/1014/2/TB_ZAINAB%20ZAKARIA%20CS%2007_5%20P01.pdf
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