NDLI: Automatic processing of Arabic text

Content Provider	IEEE Xplore Digital Library
Author	Osman, Z. Hamandi, L. Zantout, R. Sibai, F.N.
Copyright Year	2009
Description	Author affiliation: College of Computer and Info Sciences, Prince Sultan University, Riyadh, KSA (Zantout, R.) \|\| Electrical and Computer Engineering, American University of Beirut, Lebanon (Hamandi, L.) \|\| Computer Systems Design, College of IT, UAE University, Al Ain, UAE (Sibai, F.N.) \|\| Electrical Engineering, Beirut Arab University, Lebanon (Osman, Z.)
Abstract	Automatic recognition of printed and handwritten documents remains an active area of research. Arabic is one of the languages that present special problems. Arabic is cursive and therefore necessitates a segmentation process to determine the boundaries of a character. Arabic characters consist of multiple disconnected parts. Dots and Diacritics are used in many Arabic characters and can appear above or below the main body of the character. In Arabic, the same letter has up to four different forms depending on where it appears in the word and depending on the letters that are adjacent to it. In this paper, a novel approach is described that recognizes Arabic script documents. The method starts by preprocessing which involves binarization, noise reduction, and thinning. The text is then segmented into separate lines. Characters are then segmented by determining bifurcation points that are near the baseline. Segmented characters are then compared to prestored templates to identify the best match. The template comparisons are based on central moments, Hu moments, and Invariant moments. The method is proven to work satisfactorily for scanned printed Arabic text. The paper concludes with a discussion of the drawbacks of the method, and a description of possible solutions.
Starting Page	140
Ending Page	144
File Size	658950
Page Count	5
File Format	PDF
ISBN	9781424456987
e-ISBN	9781424457007
DOI	10.1109/IIT.2009.5413793
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-15
Publisher Place	United Arab Emirates
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical Character Recognition Noise reduction Bifurcation Feature Extraction Educational institutions Optical character recognition software Character recognition Handwriting recognition Design engineering Office automation Text recognition Arabic Feature extraction
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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