Skew detection and correction of mushaf Al-Quran script using hough transform

Document skew detection and correction is mainly one of base preprocessing steps in the document analysis. Correction of the skewed scanned images is critical because it has a direct impact on image quality. In this paper, the authors proposed a method for skew detection and correction for Mushaf Al...

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Main Authors: Bafjaish, Salem Saleh, Azmi, Mohd Sanusi, Al-Mhiqani, Mohammed Nasser, Radzid, Amirul Ramzani, Mahdin, Hairulnizam
Format: Article
Language:English
Published: The Science and Information (SAI) Organization Limited 2018
Subjects:
Online Access:http://eprints.uthm.edu.my/5818/1/AJ%202018%20%28592%29.pdf
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author Bafjaish, Salem Saleh
Azmi, Mohd Sanusi
Al-Mhiqani, Mohammed Nasser
Radzid, Amirul Ramzani
Mahdin, Hairulnizam
author_facet Bafjaish, Salem Saleh
Azmi, Mohd Sanusi
Al-Mhiqani, Mohammed Nasser
Radzid, Amirul Ramzani
Mahdin, Hairulnizam
author_sort Bafjaish, Salem Saleh
collection UTHM
description Document skew detection and correction is mainly one of base preprocessing steps in the document analysis. Correction of the skewed scanned images is critical because it has a direct impact on image quality. In this paper, the authors proposed a method for skew detection and correction for Mushaf Al-Quran image pages based on Hough transform method. The technique uses Hough transform lines detection for calculating the skew angulation. It works for different version of Mushaf AlQuran image pages which has skewed text zones. Moreover, it can detect and correct the skew angle in the range between 20 degrees. Experiment conducted on different Mushaf Al-Quran image pages shows the accuracy of the method.
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spelling uthm.eprints-58182022-01-24T01:25:01Z http://eprints.uthm.edu.my/5818/ Skew detection and correction of mushaf Al-Quran script using hough transform Bafjaish, Salem Saleh Azmi, Mohd Sanusi Al-Mhiqani, Mohammed Nasser Radzid, Amirul Ramzani Mahdin, Hairulnizam TK7800-8360 Electronics Document skew detection and correction is mainly one of base preprocessing steps in the document analysis. Correction of the skewed scanned images is critical because it has a direct impact on image quality. In this paper, the authors proposed a method for skew detection and correction for Mushaf Al-Quran image pages based on Hough transform method. The technique uses Hough transform lines detection for calculating the skew angulation. It works for different version of Mushaf AlQuran image pages which has skewed text zones. Moreover, it can detect and correct the skew angle in the range between 20 degrees. Experiment conducted on different Mushaf Al-Quran image pages shows the accuracy of the method. The Science and Information (SAI) Organization Limited 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/5818/1/AJ%202018%20%28592%29.pdf Bafjaish, Salem Saleh and Azmi, Mohd Sanusi and Al-Mhiqani, Mohammed Nasser and Radzid, Amirul Ramzani and Mahdin, Hairulnizam (2018) Skew detection and correction of mushaf Al-Quran script using hough transform. (IJACSA) International Journal of Advanced Computer Science and Applications, 9 (8). pp. 402-409. ISSN 2156-5570 https://dx.doi.org/10.14569/IJACSA.2018.090852
spellingShingle TK7800-8360 Electronics
Bafjaish, Salem Saleh
Azmi, Mohd Sanusi
Al-Mhiqani, Mohammed Nasser
Radzid, Amirul Ramzani
Mahdin, Hairulnizam
Skew detection and correction of mushaf Al-Quran script using hough transform
title Skew detection and correction of mushaf Al-Quran script using hough transform
title_full Skew detection and correction of mushaf Al-Quran script using hough transform
title_fullStr Skew detection and correction of mushaf Al-Quran script using hough transform
title_full_unstemmed Skew detection and correction of mushaf Al-Quran script using hough transform
title_short Skew detection and correction of mushaf Al-Quran script using hough transform
title_sort skew detection and correction of mushaf al quran script using hough transform
topic TK7800-8360 Electronics
url http://eprints.uthm.edu.my/5818/1/AJ%202018%20%28592%29.pdf
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