Advancements and Challenges in Arabic Optical Character Recognition: A Comprehensive Survey

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Mahmoud SalahEldin Kasem, Mohamed Mahmoud, Hyun-Soo Kang
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引用次数: 0

Abstract

Optical character recognition (OCR) is a vital process that involves the extraction of handwritten or printed text from scanned or printed images, converting it into a format that can be understood and processed by machines. The automatic extraction of text through OCR plays a crucial role in digitizing documents, enhancing productivity, and preserving historical records. This paper offers an exhaustive review of contemporary applications, methodologies, and challenges associated with Arabic OCR. A thorough analysis is conducted on prevailing techniques utilized throughout the OCR process, with a dedicated effort to discern the most efficacious approaches that demonstrate enhanced outcomes. To ensure a thorough evaluation, a meticulous keyword-search methodology is adopted, encompassing a comprehensive analysis of articles relevant to Arabic OCR. In addition to presenting cutting-edge techniques and methods, this paper identifies research gaps within the realm of Arabic OCR. We shed light on potential areas for future exploration and development, thereby guiding researchers toward promising avenues in the field of Arabic OCR. The outcomes of this study provide valuable insights for researchers, practitioners, and stakeholders involved in Arabic OCR, ultimately fostering advancements in the field and facilitating the creation of more accurate and efficient OCR systems for the Arabic language.
阿拉伯语光学字符识别的进展与挑战:综述
光学字符识别(OCR)是一个至关重要的过程,它涉及从扫描或打印图像中提取手写或打印文本,并将其转换为机器可以理解和处理的格式。通过OCR自动提取文本在数字化文档、提高工作效率和保存历史记录方面起着至关重要的作用。本文提供了一个详尽的审查当代应用,方法,并与阿拉伯语OCR相关的挑战。对整个OCR过程中使用的流行技术进行了彻底的分析,并致力于识别最有效的方法,以展示增强的结果。为了确保全面的评估,采用了细致的关键字搜索方法,包括对与阿拉伯语OCR相关的文章的全面分析。除了介绍尖端技术和方法外,本文还确定了阿拉伯语OCR领域内的研究差距。我们阐明了未来勘探和开发的潜在领域,从而指导研究人员走向阿拉伯语OCR领域的有前途的途径。本研究的结果为阿拉伯语OCR的研究人员、从业人员和利益相关者提供了有价值的见解,最终促进了该领域的进步,并促进了为阿拉伯语创建更准确、更高效的OCR系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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