A review of Arabic optical character recognition techniques & performance

Abstract

The Artificial intelligence one of the most perspective and interesting research area that takes attention from many researchers. Several studies focused the interest in Optical Character Recognition, which is computer software designed for converting images with text into machine processed text. These OCR systems available for several languages including Arabic, Arabic OCR has been developed and improved over decades, which ultimately causes to a huge number quantity of approaches with robust results with high, in some cases about 99%, while using deep learning in Arabic OCR can results up to 100%accuracy with short time and less resources to process the image. The characteristics of Arabic text cause more errors than in English text in OCR. The aim of this paper is to analyze the related works and issues in Arabic language OCRs. The analysis results show that existing OCRs within implementation with other application exhibit defects, or at least just their subsets, such as low-resolution inputs and video-based inputs. Accordingly, it is necessary to review existing approaches that have reliable results. In addition, the review of deep learning for Arabic OCR systems and researches is very important and useful. This paper presents a literature review on the existing systems Arabic text recognition, consists of a typical mechanism, lists the differences, advantages, and disadvantages that help in adopting or expanding these systems in accordance with modern requirements.