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An Efficient Scheme for Tilt Correction in Arabic OCR System [PDF]

International Conference on Computer Graphics, Imaging and Visualization (CGIV'05), 2005
Preprocessing stage is required in almost every image processing application ranging from biometric analysis to document image analysis. An input image or information need to be normalized and converted into format acceptable by OCR (optical character recognition) system.
Sarfraz, M., Shahab, S.A.
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Thinning algorithms for Arabic OCR

Proceedings of IEEE Pacific Rim Conference on Communications Computers and Signal Processing, 2002
The development of effective thinning algorithms for the purpose of development of Arabic OCR (optical character recognition) is considered. Two parallel thinning algorithms are presented. One is based on local operations to detect edge points, end-points, and break-points.
M. Tellache, M. Sid-Ahmed, B. Abaza
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AVOCR: Arabic video OCR

2010 5th International Symposium On I/V Communications and Mobile Network, 2010
Nowadays the majority of TV channels are performing digitization of their archival materials. The digitization enhances preservation of records and makes the access to documents easier. However, when the quantity of documents become important the digitization is not enough to insure an efficient access.
M. Ben Halima, H. Karray, A. M. Alimi
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A segmentation-free approach to Arabic and Urdu OCR

SPIE Proceedings, 2013
In this paper, we present a generic Optical Character Recognition system for Arabic script languages called Nabocr. Nabocr uses OCR approaches specific for Arabic script recognition. Performing recognition on Arabic script text is relatively more difficult than Latin text due to the nature of Arabic script, which is cursive and context sensitive ...
Nazly Sabbour, Faisal Shafait
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Space Anomalies in OCRs for Arabic Like Scripts

2018 IEEE 2nd International Workshop on Arabic and Derived Script Analysis and Recognition (ASAR), 2018
This paper investigates and analyses the nature of errors occurring in Optical Character Recognition (OCR) for Arabic-like scripts. Existing research on the area of OCR for Arabic-like scripts often focuses on achieving the best performance in terms of character error rates.
Riaz Ahmad 0001, Muhammad Zeshan Afzal, Sheikh Faisal Rashid, Marcus Liwicki, Andreas Dengel 0001   +4 more
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Omnifont and unlimited-vocabulary OCR for English and Arabic

Proceedings of the Fourth International Conference on Document Analysis and Recognition, 2002
The authors present a set of techniques for omnifont, unlimited-vocabulary OCR, within the context of a system based on hidden Markov models (HMM). First, they address the issue of how to perform OCR on omnifont and multi-style data, such as plain and italic, without the need to have a separate model for each style.
Issam Bazzi, Christopher LaPre, John Makhoul, Christopher Raphael, Richard M. Schwartz   +4 more
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Synthetic data for Arabic OCR system development

Proceedings of Sixth International Conference on Document Analysis and Recognition, 2002
A system for the automatic generation of synthetic databases for the development or evaluation of Arabic word or text recognition systems (Arabic OCR) is presented. The proposed system works without any scanning of printed paper. Firstly Arabic text has to be typeset using a standard typesetting system.
Volker Märgner, Mario Pechwitz
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Arabic OCR Based on Image Invariants

Geometric Modeling and Imaging--New Trends (GMAI'06), 2006
Optical character recognition (OCR) is an area of interest for converting hard copies of written information, as in faxed or scanned documents. In this paper, we compare two common image invariant methods in OCR, the invariant central moments (NCM) and the normalized Fourier descriptors (NFD) of the character.
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An arabic OCR using neural network classifiers

1995
A typewritten Arabic OCR (Optical Character Recognition system) is introduced. The system automatically predicts the size of the font, and uses it in separating lines, words and subwords. Then, it scans the text in a way similar to what the Arabic readers do to recognize and segment the different characters. A set of nine Neural Network modules is used
Hazem M. Raafat, Gasser Auda
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A Serial Combination of Neural Network for Arabic OCR

2014
Today, handwriting recognition is one of the most challenging tasks and exciting areas of search in computer science. Indeed, despite the growing interest in this field, no satisfactory solution is available. For this reason Multiple Classifier Systems (MCS) based on the combination of outputs of a set of different classifiers have been proposed as a ...
Leila Chergui, Maâmar Kef
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