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Segmentation-free approach with texture analysis forms the basis of object recognition and classification in several domains, one of these domains is old Arabic manuscript recognition. The basis of this approach is to analyze the texture structure of the document image independent from its content, author writing style...etc. The main objective is to propose an automatic system for recognizing and annotating the undated old Arabic document manuscripts in 4 different ages: Contemporary (Modern), Ottoman, Mamluk, and ages before Mamluk. The system has been tested by 129 different Arabic…mehr

Produktbeschreibung
Segmentation-free approach with texture analysis forms the basis of object recognition and classification in several domains, one of these domains is old Arabic manuscript recognition. The basis of this approach is to analyze the texture structure of the document image independent from its content, author writing style...etc. The main objective is to propose an automatic system for recognizing and annotating the undated old Arabic document manuscripts in 4 different ages: Contemporary (Modern), Ottoman, Mamluk, and ages before Mamluk. The system has been tested by 129 different Arabic manuscripts documents taken from Dar Al-Kotob Al-Masria Library and Leiden University Arabic manuscript collections. The results yield to 95.7% correct annotation for dated Arabic manuscript and 92.3 % for undated Arabic manuscripts.
Autorenporträt
Ahmad Abd Al Aziz, PhD.,PhD.is a lecturer at British University in Egypt (BUE. He gained PhD Degree of social sciences in 2014 from Ain Shams University and second PhD Degree of computer science in field of computational linguistics in 2016 from Cairo University. he published a number of researches aiming to apply computation on social sciences.