Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran

Recognition by segmentation of Arabic characters on scanned images has enabled many applications such as recognition for characters in certain volume of documents, automatic sorting of postal mail (in certain countries) and convenient editing of previously printed documents. This paper provides a co...

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Main Author: Amran, Mohd Firdaus
Format: Thesis
Language:English
Published: 2009
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/65814/1/65814.pdf
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spelling my-uitm-ir.658142022-09-26T07:11:28Z Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran 2009 Amran, Mohd Firdaus Study and teaching Language of the Qurʼan Recognition by segmentation of Arabic characters on scanned images has enabled many applications such as recognition for characters in certain volume of documents, automatic sorting of postal mail (in certain countries) and convenient editing of previously printed documents. This paper provides a comprehensive review of method in segmenting focusing on source of one main document that is Al-Quran. Quran in Islamic definition is the sacred writings of Islam revealed by God to the prophet Muhammad during his life at Mecca and Medina [1]. It has been written in Arabic as it was developed in that region. As Islam in become one of the biggest religious in the globe is known have many race in different country that believe as their manual of life. Research will provide segmentation rates and description of algorithm for the approaches discussed. It describes background on the field, discussion of the methods, and future research directions. 2009 Thesis https://ir.uitm.edu.my/id/eprint/65814/ https://ir.uitm.edu.my/id/eprint/65814/1/65814.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Ismail, Marina
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Ismail, Marina
topic Study and teaching
Language of the Qurʼan
spellingShingle Study and teaching
Language of the Qurʼan
Amran, Mohd Firdaus
Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran
description Recognition by segmentation of Arabic characters on scanned images has enabled many applications such as recognition for characters in certain volume of documents, automatic sorting of postal mail (in certain countries) and convenient editing of previously printed documents. This paper provides a comprehensive review of method in segmenting focusing on source of one main document that is Al-Quran. Quran in Islamic definition is the sacred writings of Islam revealed by God to the prophet Muhammad during his life at Mecca and Medina [1]. It has been written in Arabic as it was developed in that region. As Islam in become one of the biggest religious in the globe is known have many race in different country that believe as their manual of life. Research will provide segmentation rates and description of algorithm for the approaches discussed. It describes background on the field, discussion of the methods, and future research directions.
format Thesis
qualification_level Bachelor degree
author Amran, Mohd Firdaus
author_facet Amran, Mohd Firdaus
author_sort Amran, Mohd Firdaus
title Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran
title_short Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran
title_full Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran
title_fullStr Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran
title_full_unstemmed Recognizing Arabic alphabet by segmentation in Quran document / Mohd Firdaus Amran
title_sort recognizing arabic alphabet by segmentation in quran document / mohd firdaus amran
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Computer and Mathematical Sciences
publishDate 2009
url https://ir.uitm.edu.my/id/eprint/65814/1/65814.pdf
_version_ 1783735579572174848