NDLI: Optical character recognition of arabic printed text

Content Provider	IEEE Xplore Digital Library
Author	Taha, S. Babiker, Y. Abbas, M.
Copyright Year	2012
Description	Author affiliation: Electrical and Electronics Engineering Department, University of Khartoum, Sudan (Taha, S.; Babiker, Y.; Abbas, M.)
Abstract	Optical character recognition (OCR) systems improve human- machine interaction. They are widely used in many areas such as editing and storing previously printed or handwritten documents. Much of research has been done regarding the identification of Latin, Japanese and Chinese characters. However, very little investigation has been performed regarding Arabic recognition. Probably the reason is limitation of IT activities in Arabic speaking countries and the difficulty and complexity of Arabic characters identification compared to the others. More difficulties are introduced from the cursive nature of Arabic text. In this paper, a technique has been employed to segment printed Arabic text in order to separate the Arabic characters and then extracting powerful features for each to be recognized. In-order to recognize characters, those features are then compared with a pre-prepared database fields. Although the database was prepared from characters written in Time New Roman font, experimental results show the relatively high accuracy of the method developed when it is tested on several sizes of several fonts beside Time New Roman font.
Starting Page	235
Ending Page	240
File Size	726373
Page Count	6
File Format	PDF
ISBN	9781467351584
e-ISBN	9781467351607
DOI	10.1109/SCOReD.2012.6518645
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-05
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Segmentation Feature extraction Optical character recognition (OCR) Arabic characters Recognition OCR
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Bilingual OCR system for printed documents in Malayalam and English

Segmentation-based, omnifont printed Arabic character recognition without font identification

Efficient recognition of machine printed Arabic text using partial segmentation and Hausdorff distance

Automated system for Arabic optical character recognition

Study on Printed Tibetan Character Recognition

Segmentation in Malayalam OCR — Handling broken characters using active contour model

An Ocr system for printed Nasta'liq script: A segmentation based approach

AVOCR: Arabic video OCR

CSM-based feature extraction for degraded machine printed character recognition

Optical character recognition of arabic printed text

Similar Documents

Bilingual OCR system for printed documents in Malayalam and English

Segmentation-based, omnifont printed Arabic character recognition without font identification

Efficient recognition of machine printed Arabic text using partial segmentation and Hausdorff distance

Automated system for Arabic optical character recognition

Study on Printed Tibetan Character Recognition

Segmentation in Malayalam OCR — Handling broken characters using active contour model

An Ocr system for printed Nasta'liq script: A segmentation based approach

AVOCR: Arabic video OCR

CSM-based feature extraction for degraded machine printed character recognition

Optical character recognition of arabic printed text