Figure 1 illustrates the characteristics of Arabic printed text that contribute to the inadequate development of Arabic script recognition. Therefore, this study will deal only with Arabic printed text. Although handwritten script is significantly more challenging than printed Arabic text for OCR, Arabic printed text OCR still poses significant challenges ( Alghamdi et al., 2016). Previous research on text recognition has focused primarily on Latin scripts, such as English and Chinese, and it has not been until the last two decades that recognition of non-Latin scripts, such as Arabic, have been researched ( Alginahi, 2013). In each stage, specific techniques are applied for more details, see Khorsheed (2002). Generally, the process for developing OCR systems involves five stages: pre-processing, segmentation, feature extraction, classification and post-processing. 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). 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).
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