Open Access

REVIEW

Arabic Optical Character Recognition: A Review

by Salah Alghyaline^*

Computer Science Department, The World Islamic Sciences and Education University, Amman, 1101-11947, Jordan

* Corresponding Author: Salah Alghyaline. Email:

Computer Modeling in Engineering & Sciences 2023, 135(3), 1825-1861. https://doi.org/10.32604/cmes.2022.024555

Received 01 June 2022; Accepted 16 August 2022; Issue published 23 November 2022

Abstract

This study aims to review the latest contributions in Arabic Optical Character Recognition (OCR) during the last decade, which helps interested researchers know the existing techniques and extend or adapt them accordingly. The study describes the characteristics of the Arabic language, different types of OCR systems, different stages of the Arabic OCR system, the researcher’s contributions in each step, and the evaluation metrics for OCR. The study reviews the existing datasets for the Arabic OCR and their characteristics. Additionally, this study implemented some preprocessing and segmentation stages of Arabic OCR. The study compares the performance of the existing methods in terms of recognition accuracy. In addition to researchers’ OCR methods, commercial and open-source systems are used in the comparison. The Arabic language is morphologically rich and written cursive with dots and diacritics above and under the characters. Most of the existing approaches in the literature were evaluated on isolated characters or isolated words under a controlled environment, and few approaches were tested on page-level scripts. Some comparative studies show that the accuracy of the existing Arabic OCR commercial systems is low, under 75% for printed text, and further improvement is needed. Moreover, most of the current approaches are offline OCR systems, and there is no remarkable contribution to online OCR systems.

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Keywords

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