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Erschienen in: Neural Computing and Applications 7/2021

17.07.2020 | Review

Automatic recognition of handwritten Arabic characters: a comprehensive review

verfasst von: Hossam Magdy Balaha, Hesham Arafat Ali, Mahmoud Badawy

Erschienen in: Neural Computing and Applications | Ausgabe 7/2021

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Abstract

The paper is a comprehensive review of the current research trends in the area of Arabic language especially state-of-the-art approaches to highlight the current status of diverse research aspects of that area to facilitate the adaption and extension of previous systems into new applications and systems. The Arabic language has deep, widespread and unexplored scope to research although the tremendous effort and researches that had been done previously. Modern state-of-the-art methods and approaches with fewer errors are required according to the high speed of hardware and technology development. The focus of this article will be on the offline Arabic handwritten text recognition as it is one of the most important topics in the Arabic scope. The main objective of this paper is critically analyzing the current researches to identify the problem areas and challenges faced by the previous researchers. This identification is intended to provide many recommendations for future advances in the area. It also compares and contrasts technical challenges, methods and the performances of handwritten text recognition previous researches works. It summarizes the critical problems and enumerates issues that should be considered when addressing these tasks. It also shows some of the Arabic datasets that can be used as inputs and benchmarks for training, testing and comparisons. Finally, it provides a fundamental comparison and discussion of some of the remaining open problems and trends in that field.

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Metadaten
Titel
Automatic recognition of handwritten Arabic characters: a comprehensive review
verfasst von
Hossam Magdy Balaha
Hesham Arafat Ali
Mahmoud Badawy
Publikationsdatum
17.07.2020
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-05137-6

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