This paper proposes a novel an effective approach to classify the damage in Ancient Arabic manuscripts through Damage Manuscripts Classification (DMC) Model; into two types, each type has spatial model. The first type is Fading Text Color (FTC) Model, and the second is Missing Part of Text (MPT) Model. For the first type, which is the Fading text color, it is done through (FTC) Model, where segmentation, contour strength and contour size algorithms were applied. As for the second type, we applied some segmentation algorithms to separate image of damaged manuscripts into foreground and background. Segmentation by thresholding applied on background to detect if there are missing in text to complete it based on database which we had prepared for this purpose including the handwritten Arabic fonts and the forms of letters in different styles such as Naskh , Reqaa,..etc. detection of style algorithm is also used to determine the style of missing text according to the same database , then digital restoration applied to the image. Applying Pre-processes on the used data yields good classifications’ results. The contribution of this work is the introduction of synthetic features that enhance the classification performance. For testing purposes, two famous books from the Islamic literature are used: 1) pages of the Ottoman Quran and 2) Some Quran verses in Naskh script.
تهدف هذه الدراسة إلى محتوي المخطوط العربي وکيفية الحفلظ عليه من خالل صيانته عن العوامل التي يتعرض لها وقد تؤدي إلي إتالف جزء منه أو الحيلولة دون اإلستفاده القصوي من محتوي تلک المخطوطات وما تشتمل عليه من کنوز علمية وتاريخية ودينيه ال تقدر بثمن. ومن هنا وجب علينا الربط بين العلوم الحديثة کمعالجة الصوروتعلم األله )learning Machine )في ترميم ومعالجة مظاهر التلف في المخطوط والتي تن ت ج عن التقادم الزمني أو االستخدام الغير صحيح وأحيانا نتيجة للتداول بين المستخدمين. وقدمت هذه الدراسة نموذجا لتصنيف نوع التلف بالمخطوط العربي أوتوماتيکيا ودون الحاجة للعامل البشري ومن ثم فقد شملت تلک الدراسة أبضا علي کيفية جديدة للترميم اإللکتروني ألکثر أنواع التلف انتشارا في المخطوطات العربية
Hassan, A. A., Elrefai, F., Halwa, A., & Gadelrab, H. (2022). CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS. Journal of Al-Azhar University Engineering Sector, 17(63), 612-624. doi: 10.21608/auej.2022.233845
MLA
Al Amira A. Hassan; Fawzy I. Elrefai; Ali A. Halwa; Hany Gadelrab. "CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS". Journal of Al-Azhar University Engineering Sector, 17, 63, 2022, 612-624. doi: 10.21608/auej.2022.233845
HARVARD
Hassan, A. A., Elrefai, F., Halwa, A., Gadelrab, H. (2022). 'CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS', Journal of Al-Azhar University Engineering Sector, 17(63), pp. 612-624. doi: 10.21608/auej.2022.233845
VANCOUVER
Hassan, A. A., Elrefai, F., Halwa, A., Gadelrab, H. CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS. Journal of Al-Azhar University Engineering Sector, 2022; 17(63): 612-624. doi: 10.21608/auej.2022.233845
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