Next Article in Journal
Deriving Quantitative Crystallographic Information from the Wavelength-Resolved Neutron Transmission Analysis Performed in Imaging Mode
Next Article in Special Issue
Transcription of Spanish Historical Handwritten Documents with Deep Neural Networks
Previous Article in Journal
In-Situ Imaging of Liquid Phase Separation in Molten Alloys Using Cold Neutrons
Previous Article in Special Issue
DocCreator: A New Software for Creating Synthetic Ground-Truthed Document Images

A Holistic Technique for an Arabic OCR System

Department of Electronics and Electrical Communications, Cairo University, Giza 12613, Egypt
Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Faculty of Computers & Information, Cairo University, Giza 12613, Egypt
Author to whom correspondence should be addressed.
Received: 30 October 2017 / Revised: 18 December 2017 / Accepted: 22 December 2017 / Published: 27 December 2017
(This article belongs to the Special Issue Document Image Processing)
Analytical based approaches in Optical Character Recognition (OCR) systems can endure a significant amount of segmentation errors, especially when dealing with cursive languages such as the Arabic language with frequent overlapping between characters. Holistic based approaches that consider whole words as single units were introduced as an effective approach to avoid such segmentation errors. Still the main challenge for these approaches is their computation complexity, especially when dealing with large vocabulary applications. In this paper, we introduce a computationally efficient, holistic Arabic OCR system. A lexicon reduction approach based on clustering similar shaped words is used to reduce recognition time. Using global word level Discrete Cosine Transform (DCT) based features in combination with local block based features, our proposed approach managed to generalize for new font sizes that were not included in the training data. Evaluation results for the approach using different test sets from modern and historical Arabic books are promising compared with state of art Arabic OCR systems. View Full-Text
Keywords: Arabic OCR systems; holistic OCR approach; holistic OCR features; lexicon reduction Arabic OCR systems; holistic OCR approach; holistic OCR features; lexicon reduction
Show Figures

Figure 1

MDPI and ACS Style

Nashwan, F.M.A.; Rashwan, M.A.A.; Al-Barhamtoshy, H.M.; Abdou, S.M.; Moussa, A.M. A Holistic Technique for an Arabic OCR System. J. Imaging 2018, 4, 6.

AMA Style

Nashwan FMA, Rashwan MAA, Al-Barhamtoshy HM, Abdou SM, Moussa AM. A Holistic Technique for an Arabic OCR System. Journal of Imaging. 2018; 4(1):6.

Chicago/Turabian Style

Nashwan, Farhan M.A., Mohsen A.A. Rashwan, Hassanin M. Al-Barhamtoshy, Sherif M. Abdou, and Abdullah M. Moussa 2018. "A Holistic Technique for an Arabic OCR System" Journal of Imaging 4, no. 1: 6.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop