research-article

Printed Arabic Text Database for Automatic Recognition Systems

Authors:

Hassina Bouressace,

Janos CsirikAuthors Info & Claims

ICCTA '19: Proceedings of the 2019 5th International Conference on Computer and Technology Applications

Pages 107 - 111

https://doi.org/10.1145/3323933.3324082

Published: 16 April 2019 Publication History

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Abstract

Document image analysis and recognition are important topics in artificial intelligence as they are necessary for the retrieval of documents. Hence, the availability of a database with good script samples is a key requirement for machine-learning processes. Good printed text databases exist for Latin languages. However, there is a lack of databases with Arabic samples. This paper presents a new comprehensive database called PATD (Printed Arabic Text Database), which contains eight hundred and ten images scanned in grayscale format and different resolutions, leading to two thousand and nine hundred and fifty-four images (smartphone-captured images) under varying capture conditions (blurred, at different angles and in different light). It is based on ten newspapers created with different structures, and an open-vocabulary, multi-font, multi-size and multi-style text. The database is described in detail and it is intended for the research community.

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Cited By

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Gaashan KYounes M(2024)Deep Learning-based Arabic Optical Character Recognition: A New Comprehensive Dataset at Character and Word Levels2024 15th International Conference on Information and Communication Systems (ICICS)10.1109/ICICS63486.2024.10638273(1-6)Online publication date: 13-Aug-2024
https://doi.org/10.1109/ICICS63486.2024.10638273
Bouressace H(2023)Computational Analysis of Printed Arabic Text Database for Natural Language ProcessingCognitive Studies | Études cognitives10.11649/cs.3027Online publication date: 31-Dec-2023
https://doi.org/10.11649/cs.3027
Khan SKhan HNazir S(2021)Offline Pashto Characters Dataset for OCR SystemsSecurity and Communication Networks10.1155/2021/35438162021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/3543816
Show More Cited By

Index Terms

Printed Arabic Text Database for Automatic Recognition Systems
1. Applied computing
  1. Document management and text processing

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ICCTA '19: Proceedings of the 2019 5th International Conference on Computer and Technology Applications

April 2019

206 pages

ISBN:9781450371810

DOI:10.1145/3323933

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Istanbul Technical University: Istanbul Technical University

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Association for Computing Machinery

New York, NY, United States

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Published: 16 April 2019

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ICCTA 2019: 2019 5th International Conference on Computer and Technology Applications

April 16 - 17, 2019

Istanbul, Turkey

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Gaashan KYounes M(2024)Deep Learning-based Arabic Optical Character Recognition: A New Comprehensive Dataset at Character and Word Levels2024 15th International Conference on Information and Communication Systems (ICICS)10.1109/ICICS63486.2024.10638273(1-6)Online publication date: 13-Aug-2024
https://doi.org/10.1109/ICICS63486.2024.10638273
Bouressace H(2023)Computational Analysis of Printed Arabic Text Database for Natural Language ProcessingCognitive Studies | Études cognitives10.11649/cs.3027Online publication date: 31-Dec-2023
https://doi.org/10.11649/cs.3027
Khan SKhan HNazir S(2021)Offline Pashto Characters Dataset for OCR SystemsSecurity and Communication Networks10.1155/2021/35438162021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/3543816
Bouressace HCsirik J(2019)A Convolutional Neural Network for Arabic Document Analysis2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)10.1109/ISSPIT47144.2019.9001779(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ISSPIT47144.2019.9001779

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Printed Arabic text database (PATDB) for research and benchmarking

A New Arabic Printed Text Image Database and Evaluation Protocols

Benchmark database and GUI environment for printed Arabic text recognition research

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