Features Extraction of Arabic Calligraphy using extended Triangle Model for Digital Jawi Paleography Analysis
The style of writing or calligraphy applied in ancient manuscripts gives useful information to paleographers. The information helps paleographer to identify date, writer, number of writers, place of origin, and the originality of manuscripts. This information is known as features. The features f...
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my.utem.eprints.119242015-05-28T04:21:14Z http://eprints.utem.edu.my/id/eprint/11924/ Features Extraction of Arabic Calligraphy using extended Triangle Model for Digital Jawi Paleography Analysis Mohd Sanusi, Azmi Muda, A. K. Khadijah Wan, Mohd Ghazali T Technology (General) The style of writing or calligraphy applied in ancient manuscripts gives useful information to paleographers. The information helps paleographer to identify date, writer, number of writers, place of origin, and the originality of manuscripts. This information is known as features. The features from characters, tangent value, dominant background and also Grey-Level Co-occurrence Matrix (GLCM) have been used in this field of research. A novel technique was proposed for digital Jawi Paleography. Jawi is the original Malay writing based on Arabic characters. The technique proposed models triangles on images and extracts features from them. The features are used for classification. In this paper, new features for the Triangle Model are proposed. Also, the implementation of four zones is reported. The number of features has been extended from 12 to 45. For validation of proposed algorithm, 60,000:20,000 training and testing data from Hoda digit dataset has been prepared, selected randomly for 10 rounds of testing. For further verification, two Supervised Machine Learning (SML) and three Unsupervised Machine Learning (UML) algorithms were experimented. These experiments were conducted using a new Arabic calligraphy dataset that was set up from 1,225 Arabic letters taken from calligraphy books. From the data, SML experiments were conducted with the ratio of 807:408 for training and testing. Whereas for the UML, three classifiers were tested on 30 images of Arabic calligraphy dataset. Results from the tests prove that the Triangle Model technique can successfully be used in digital paleography of Jawi characters. Dynamic Publishers, Inc., USA 2013 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/11924/1/Paper148.pdf Mohd Sanusi, Azmi and Muda, A. K. and Khadijah Wan, Mohd Ghazali (2013) Features Extraction of Arabic Calligraphy using extended Triangle Model for Digital Jawi Paleography Analysis. International Journal of Computer Information Systems and Industrial Management Applications. pp. 696-703. ISSN 2150-7988 |
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T Technology (General) Mohd Sanusi, Azmi Muda, A. K. Khadijah Wan, Mohd Ghazali Features Extraction of Arabic Calligraphy using extended Triangle Model for Digital Jawi Paleography Analysis |
description |
The style of writing or calligraphy applied in ancient
manuscripts gives useful information to paleographers. The
information helps paleographer to identify date, writer, number
of writers, place of origin, and the originality of manuscripts.
This information is known as features. The features from
characters, tangent value, dominant background and also
Grey-Level Co-occurrence Matrix (GLCM) have been used in
this field of research. A novel technique was proposed for digital
Jawi Paleography. Jawi is the original Malay writing based on
Arabic characters. The technique proposed models triangles on
images and extracts features from them. The features are used
for classification. In this paper, new features for the Triangle
Model are proposed. Also, the implementation of four zones is
reported. The number of features has been extended from 12 to
45. For validation of proposed algorithm, 60,000:20,000 training
and testing data from Hoda digit dataset has been prepared,
selected randomly for 10 rounds of testing. For further
verification, two Supervised Machine Learning (SML) and three
Unsupervised Machine Learning (UML) algorithms were
experimented. These experiments were conducted using a new
Arabic calligraphy dataset that was set up from 1,225 Arabic
letters taken from calligraphy books. From the data, SML
experiments were conducted with the ratio of 807:408 for
training and testing. Whereas for the UML, three classifiers
were tested on 30 images of Arabic calligraphy dataset. Results
from the tests prove that the Triangle Model technique can
successfully be used in digital paleography of Jawi characters. |
format |
Article |
author |
Mohd Sanusi, Azmi Muda, A. K. Khadijah Wan, Mohd Ghazali |
author_facet |
Mohd Sanusi, Azmi Muda, A. K. Khadijah Wan, Mohd Ghazali |
author_sort |
Mohd Sanusi, Azmi |
title |
Features Extraction of Arabic Calligraphy using
extended Triangle Model for Digital Jawi
Paleography Analysis |
title_short |
Features Extraction of Arabic Calligraphy using
extended Triangle Model for Digital Jawi
Paleography Analysis |
title_full |
Features Extraction of Arabic Calligraphy using
extended Triangle Model for Digital Jawi
Paleography Analysis |
title_fullStr |
Features Extraction of Arabic Calligraphy using
extended Triangle Model for Digital Jawi
Paleography Analysis |
title_full_unstemmed |
Features Extraction of Arabic Calligraphy using
extended Triangle Model for Digital Jawi
Paleography Analysis |
title_sort |
features extraction of arabic calligraphy using
extended triangle model for digital jawi
paleography analysis |
publisher |
Dynamic Publishers, Inc., USA |
publishDate |
2013 |
url |
http://eprints.utem.edu.my/id/eprint/11924/1/Paper148.pdf http://eprints.utem.edu.my/id/eprint/11924/ |
_version_ |
1665905482220437504 |