受损阿拉伯语手稿的分类和数字修复

Al Amira A. Hassan, Fawzy I. Elrefai, Ali A. Halwa, Hany Gadelrab
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摘要

本文提出了一种利用破损手稿分类模型(DMC)对古代阿拉伯语手稿进行破损分类的新方法。分为两种类型,每种类型都有空间模型。第一种是文本颜色褪色模型(FTC),第二种是文本部分缺失模型(MPT)。对于第一种类型,即褪色文本颜色,通过(FTC)模型完成,其中应用了分割,轮廓强度和轮廓大小算法。对于第二种类型,我们使用一些分割算法将受损手稿图像分离为前景和背景。基于我们为此准备的数据库,包括手写的阿拉伯字体和不同风格的字母形式,如Naskh, Reqaa等,在后台应用阈值分割,检测文本中是否有缺失,并完成文本。采用风格检测算法,根据同一数据库确定缺失文本的风格,然后对图像进行数字恢复。对使用的数据进行预处理可以得到良好的分类结果。这项工作的贡献是引入了提高分类性能的综合特征。为了进行测试,我们使用了伊斯兰文学中的两本著名书籍:1)奥斯曼帝国的《古兰经》和2)纳斯克文的《古兰经》章节。手稿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS
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 . Manuscripts.
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