Arabic Calligraphy Classification using Triangle Model for Digital Jawi Paleography Analysis
Calligraphy classification of the ancient manuscripts gives useful information to paleographers. Researches on digital paleography using calligraphy are done on the manuscripts to identify unidentified place of origin, number of writers, and the date of ancient manuscripts. Information that are...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/249/1/P247.pdf http://eprints.utem.edu.my/id/eprint/249/ |
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| Institution: | Universiti Teknikal Malaysia Melaka |
| Language: | English |
| Summary: | Calligraphy classification of the ancient manuscripts
gives useful information to paleographers. Researches on digital
paleography using calligraphy are done on the manuscripts to
identify unidentified place of origin, number of writers, and the
date of ancient manuscripts. Information that are used are
features from characters, tangent value and features known as
Grey-Level Co-occurrence Matrix (GLCM). For Digital Jawi
Paleography, a novel technique is proposed based on the triangle.
This technique defines three important coordinates in the image
of each character and translates it into triangle geometry form.
The features are extracted from the triangle to represent the Jawi (Arabic writing in Malay language) characters.
Experiments have been conducted using seven Unsupervised
Machine Learning (UML) algorithms and one Supervised
Machine Learning (SML). This stage focuses on the accuracy of Arabic calligraphy classification. Hence, the model and test data are Arabic calligraphy letters taken from calligraphy books. The number of model is 711 for the UML and 1019 for the SML. Twelve features are extracted from the formed triangles used. |
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