J. Imaging 2018, 4(1), 6; https://doi.org/10.3390/jimaging4010006
A Holistic Technique for an Arabic OCR System
Farhan M. A. Nashwan 1, Mohsen A. A. Rashwan 1, Hassanin M. Al-Barhamtoshy 2
, Sherif M. Abdou 3,* and Abdullah M. Moussa 1
, Sherif M. Abdou 3,* and Abdullah M. Moussa 1
1
Department of Electronics and Electrical Communications, Cairo University, Giza 12613, Egypt
2
Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
3
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)
Abstract
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
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Share & Cite This Article
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.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
Related Articles
Article Metrics
Comments
[Return to top]
J. Imaging
EISSN 2313-433X
Published by MDPI AG, Basel, Switzerland
RSS
E-Mail Table of Contents Alert