Yarmouk Arabic OCR Dataset

Iyad Abu Doush; Faisal Aikhateeb; Anwaar Hamdi Gharibeh

doi:10.1109/CSIT.2018.8486162

Yarmouk Arabic OCR Dataset

Iyad Abu Doush
, Faisal Aikhateeb
, Anwaar Hamdi Gharibeh

Computer Science and Info Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Scopus citations

Abstract

Optical Character Recognition (OCR) is the process of recognizing characters automatically from scanned or image documents. OCR software uses machine learning to recognize characters in the document. Such software needs to pass a training phase to learn how to recognize the letters in the text. In order to implement the training phase the OCR needs to use a standard dataset. The dataset can be used to evaluate the obtained results. In this research, we propose an Arabic printed OCR dataset. To the best of our knowledge, there is no Arabic OCR dataset that is available to be used by the research community with its ground truth with a size that is suitable to build a robust Arabic OCR. The proposed dataset is extracted randomly from Wikipedia to have different topics. It consists of 4,587 Arabic articles with a total of 8,994 images.

Original language	English
Title of host publication	2018 8th International Conference on Computer Science and Information Technology, CSIT 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	150-154
Number of pages	5
ISBN (Electronic)	9781538641521
DOIs	https://doi.org/10.1109/CSIT.2018.8486162
State	Published - 8 Oct 2018
Event	8th International Conference on Computer Science and Information Technology, CSIT 2018 - Amman, Jordan Duration: 11 Jul 2018 → 12 Jul 2018

Publication series

Name	2018 8th International Conference on Computer Science and Information Technology, CSIT 2018

Conference

Conference	8th International Conference on Computer Science and Information Technology, CSIT 2018
Country/Territory	Jordan
City	Amman
Period	11/07/18 → 12/07/18

Keywords

Arabic OCR Dataset
Image Dataset
Optical Character Recognition

Access to Document

10.1109/CSIT.2018.8486162

Cite this

Doush, I. A., Aikhateeb, F., & Gharibeh, A. H. (2018). Yarmouk Arabic OCR Dataset. In 2018 8th International Conference on Computer Science and Information Technology, CSIT 2018 (pp. 150-154). Article 08486162 (2018 8th International Conference on Computer Science and Information Technology, CSIT 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSIT.2018.8486162

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title = "Yarmouk Arabic OCR Dataset",

abstract = "Optical Character Recognition (OCR) is the process of recognizing characters automatically from scanned or image documents. OCR software uses machine learning to recognize characters in the document. Such software needs to pass a training phase to learn how to recognize the letters in the text. In order to implement the training phase the OCR needs to use a standard dataset. The dataset can be used to evaluate the obtained results. In this research, we propose an Arabic printed OCR dataset. To the best of our knowledge, there is no Arabic OCR dataset that is available to be used by the research community with its ground truth with a size that is suitable to build a robust Arabic OCR. The proposed dataset is extracted randomly from Wikipedia to have different topics. It consists of 4,587 Arabic articles with a total of 8,994 images.",

keywords = "Arabic OCR Dataset, Image Dataset, Optical Character Recognition",

author = "Doush, \{Iyad Abu\} and Faisal Aikhateeb and Gharibeh, \{Anwaar Hamdi\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th International Conference on Computer Science and Information Technology, CSIT 2018 ; Conference date: 11-07-2018 Through 12-07-2018",

year = "2018",

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doi = "10.1109/CSIT.2018.8486162",

language = "English",

series = "2018 8th International Conference on Computer Science and Information Technology, CSIT 2018",

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Doush, IA, Aikhateeb, F & Gharibeh, AH 2018, Yarmouk Arabic OCR Dataset. in 2018 8th International Conference on Computer Science and Information Technology, CSIT 2018., 08486162, 2018 8th International Conference on Computer Science and Information Technology, CSIT 2018, Institute of Electrical and Electronics Engineers Inc., pp. 150-154, 8th International Conference on Computer Science and Information Technology, CSIT 2018, Amman, Jordan, 11/07/18. https://doi.org/10.1109/CSIT.2018.8486162

Yarmouk Arabic OCR Dataset. / Doush, Iyad Abu; Aikhateeb, Faisal; Gharibeh, Anwaar Hamdi.
2018 8th International Conference on Computer Science and Information Technology, CSIT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 150-154 08486162 (2018 8th International Conference on Computer Science and Information Technology, CSIT 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Yarmouk Arabic OCR Dataset

AU - Doush, Iyad Abu

AU - Aikhateeb, Faisal

AU - Gharibeh, Anwaar Hamdi

PY - 2018/10/8

Y1 - 2018/10/8

N2 - Optical Character Recognition (OCR) is the process of recognizing characters automatically from scanned or image documents. OCR software uses machine learning to recognize characters in the document. Such software needs to pass a training phase to learn how to recognize the letters in the text. In order to implement the training phase the OCR needs to use a standard dataset. The dataset can be used to evaluate the obtained results. In this research, we propose an Arabic printed OCR dataset. To the best of our knowledge, there is no Arabic OCR dataset that is available to be used by the research community with its ground truth with a size that is suitable to build a robust Arabic OCR. The proposed dataset is extracted randomly from Wikipedia to have different topics. It consists of 4,587 Arabic articles with a total of 8,994 images.

AB - Optical Character Recognition (OCR) is the process of recognizing characters automatically from scanned or image documents. OCR software uses machine learning to recognize characters in the document. Such software needs to pass a training phase to learn how to recognize the letters in the text. In order to implement the training phase the OCR needs to use a standard dataset. The dataset can be used to evaluate the obtained results. In this research, we propose an Arabic printed OCR dataset. To the best of our knowledge, there is no Arabic OCR dataset that is available to be used by the research community with its ground truth with a size that is suitable to build a robust Arabic OCR. The proposed dataset is extracted randomly from Wikipedia to have different topics. It consists of 4,587 Arabic articles with a total of 8,994 images.

KW - Arabic OCR Dataset

KW - Image Dataset

KW - Optical Character Recognition

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M3 - Conference contribution

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BT - 2018 8th International Conference on Computer Science and Information Technology, CSIT 2018

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T2 - 8th International Conference on Computer Science and Information Technology, CSIT 2018

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ER -

Yarmouk Arabic OCR Dataset

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