Hassan, A., Elrefai, F., Halwa, A., Gadelrab, H. (2022). CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS. test, 17(63), 612-624. doi: 10.21608/auej.2022.233845
Al Amira A. Hassan; Fawzy I. Elrefai; Ali A. Halwa; Hany Gadelrab. "CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS". test, 17, 63, 2022, 612-624. doi: 10.21608/auej.2022.233845
Hassan, A., Elrefai, F., Halwa, A., Gadelrab, H. (2022). 'CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS', test, 17(63), pp. 612-624. doi: 10.21608/auej.2022.233845
Hassan, A., Elrefai, F., Halwa, A., Gadelrab, H. CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS. test, 2022; 17(63): 612-624. doi: 10.21608/auej.2022.233845

CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS

Journal of Al-Azhar University Engineering Sector
Article 12, Volume 17, Issue 63, April 2022, Pages 612-624    PDF (1.45 M)
Document Type: Original Article
DOI: 10.21608/auej.2022.233845
Authors
Al Amira A. Hassan1; Fawzy I. Elrefai1; Ali A. Halwa1; Hany Gadelrab2
1System & Computers Eng., Faculty of Engineering, Al-Azhar University, Cairo, Egypt.
2Conservator at Historic Cairo Administration, Ministry of Tourism and Antiquities, Cairo, Egypt
Abstract
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
Keywords
Damaged Arabic Manuscripts; Classification; Foreground Separation; Machine Learning; Threshold Algorithm; and Digital Restoration; Missing Text; Color Fading; and Classify Damage in Manuscripts. المخطوطات العربية القديمة; نوع التلف في المخطوط; معالجة وتحسين الصور; فصل طبقات الصورة; الترميم األلکتروني; بهتان لون النص بالمخطوطات العربية; فقد جزء من النص
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