research-article

Analysis of Cursive Text Recognition Systems: A Systematic Literature Review

Authors:
Sulaiman Khan

College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar and Department of Computer Science, University of Swabi, Swabi, Pakistan

College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar and Department of Computer Science, University of Swabi, Swabi, Pakistan

0000-0003-2562-3477
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,
Shah Nazir

Department of Computer Science, University of Swabi, Swabi, Pakistan

Department of Computer Science, University of Swabi, Swabi, Pakistan

0000-0003-0126-9944
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,
Habib Ullah Khan

Department of Accounting and Information Systems, College of Business and Economics, Qatar University, Doha, Qatar

Department of Accounting and Information Systems, College of Business and Economics, Qatar University, Doha, Qatar

0000-0001-8373-2781
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ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22 Issue 7Article No.: 188pp 1–30https://doi.org/10.1145/3592600

Published:20 July 2023Publication History

ACM Transactions on Asian and Low-Resource Language Information Processing

Abstract

Regional and cultural diversities around the world have given birth to a large number of writing systems and scripts, which consist of varying character sets. Developing an optimal character recognition for such a varying and large character set is a challenging task. Unlimited variations in handwritten text due to mood swings, varying writing styles, changes in medium of writing, and many more puzzle the research community. To overcome this problem, researchers have proposed various techniques for the automatic recognition of cursive languages like Urdu, Pashto, and Arabic. With the passage of time, the field of text recognition matured, and the number of publications exponentially increased in the targeted field. It is very difficult to find all the techniques developed, calculate the time and resource consumptions, and understand the cost–benefit tradeoffs among these techniques. These tradeoffs resist making this technology able for practical use. To address these tradeoffs, this article systematic analysis to identify gaps in the literature and suggest new enhanced solution accordingly. A total of 153 of the most relevant articles from 2008 to 2022 are analyzed in this systematic literature review (SLR) work. This systematic review process shows (1) the list of techniques suggested for cursive text recognition purposes and its capabilities, (2) set of feature extraction techniques proposed, and (3) implementation tools used to design and simulate the empirical studies in this specialized field. We have also discussed the emerging trends and described their implications for the research community in this specialized domain. This systematic assessment will ultimately help researchers to perform an overview of the existing character/text recognition approaches, recognition capabilities, and time consumption and subsequently identify the areas that requires a significant attention in the near future.

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Index Terms

Analysis of Cursive Text Recognition Systems: A Systematic Literature Review
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction

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Published in
ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22, Issue 7
July 2023
422 pages
ISSN:2375-4699
EISSN:2375-4702
DOI:10.1145/3610376
Editor:
Imed Zitouni
Google, USA
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Publication History
- Published: 20 July 2023
- Online AM: 13 April 2023
- Accepted: 8 April 2023
- Revised: 3 January 2023
- Received: 13 April 2022
Published in tallip Volume 22, Issue 7

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Analysis of Cursive Text Recognition Systems: A Systematic Literature Review

ACM Transactions on Asian and Low-Resource Language Information Processing

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Data Augmentation for Offline Handwritten Text Recognition: A Systematic Literature Review

A Method of Recognition of Arabic Cursive Handwriting

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Analysis of Cursive Text Recognition Systems: A Systematic Literature Review

ACM Transactions on Asian and Low-Resource Language Information Processing

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Handwritten Cursive Jawi Character Recognition: A Survey

Data Augmentation for Offline Handwritten Text Recognition: A Systematic Literature Review

A Method of Recognition of Arabic Cursive Handwriting

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