Abstract
Purpose The aim of this paper is to experimentally evaluate the effectiveness of the state-of-the-art printed Arabic text recognition systems to determine open areas for future improvements. In addition, this paper proposes a standard protocol with a set of metrics for measuring the effectiveness of Arabic optical character recognition (OCR) systems to assist researchers in comparing different Arabic OCR approaches. Design/methodology/approach This paper describes an experiment to automatically evaluate four well-known Arabic OCR systems using a set of performance metrics. The evaluation experiment is conducted on a publicly available printed Arabic dataset comprising 240 text images with a variety of resolution levels, font types, font styles and font sizes. Findings The experimental results show that the field of character recognition for printed Arabic still requires further research to reach an efficient text recognition method for Arabic script. Originality/value To the best of the authors’ knowledge, this is the first work that provides a comprehensive automated evaluation of Arabic OCR systems with respect to the characteristics of Arabic script and, in addition, proposes an evaluation methodology that can be used as a benchmark by researchers and therefore will contribute significantly to the enhancement of the field of Arabic script recognition.
Highlights
Optical character recognition (OCR) is a technique that aims to automatically convert a machine-printed or handwritten text image into an editable text format (Alghamdi et al, 2016)
Our evaluation study is limited to the four most well-known Arabic OCR systems, namely, Automatic Reader 11.2 produced by the Sakhr Software Company; FineReader 12 produced by the ABBYY Company; Clever Page produced by RDI (Research & Development International) and Tesseract produced originally by Hewlett-Packard (HP)
Experimental results and discussion The experimental results, obtained from the evaluation experiment discussed in the previous section, are presented to analyse the effectiveness of the evaluated Arabic OCR systems in printed Arabic text recognition
Summary
Optical character recognition (OCR) is a technique that aims to automatically convert a machine-printed or handwritten text image into an editable text format (Alghamdi et al, 2016). This technique is highly desirable in various real-world applications, such as digitising learning resources to assist visually impaired people, bank cheque processing and mail sorting (Alginahi, 2013; Al-Badr and Mahmoud, 1995). The process for developing OCR systems involves five stages: pre-processing, segmentation, feature extraction, classification and post-processing. Specific techniques are applied; for more details, see Khorsheed (2002).
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