Corpus-based technique for improving Arabic OCR system

Ahmed Hussain Aliwy, Basheer Al-Sadawi

Abstract


An optical character recognition (OCR) refers to a process of converting the text document images into editable and searchable text. OCR process poses several challenges in particular in the Arabic language due to it has caused a high percentage of errors. In this paper, a method, to improve the outputs of the Arabic Optical character recognition (AOCR) Systems is suggested based on a statistical language model built from the available huge corpora. This method includes detecting and correcting non-word and real words error according to the context of the word in the sentence. The results show that the percentage of improvement in the results is up to (98%) as a new accuracy for AOCR output. 


Keywords


AOCR post-processing; Arabic optical character recognition; N-gram language model; NLP-based OCR; Non-word error; Real-word error

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DOI: http://doi.org/10.11591/ijeecs.v21.i1.pp233-241

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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