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Zoning features and 2DLSTM for urdu text-line recognition

Naz, Saeeda, Ahmed, Saad Bin, Ahmad, Riaz and Razzak, Muhammad Imran 2016, Zoning features and 2DLSTM for urdu text-line recognition, in KES2016 : 20th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, Elsevier, Amsterdam, The Netherlands, doi: 10.1016/j.procs.2016.08.084.

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Title Zoning features and 2DLSTM for urdu text-line recognition
Author(s) Naz, Saeeda
Ahmed, Saad Bin
Ahmad, Riaz
Razzak, Muhammad ImranORCID iD for Razzak, Muhammad Imran orcid.org/0000-0002-3930-6600
Conference name Knowledge Based and Intelligent Information and Engineering Systems (20th : 2016 : York, England)
Conference location York, England
Conference dates 2016/09/05 - 2016/09/07
Title of proceedings KES2016 : 20th International Conference on Knowledge Based and Intelligent Information and Engineering Systems
Publication date 2016
Total pages 7
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Summary © 2016 The Authors. Published by Elsevier B.V. Recognition of Urdu cursive script is a challenging task due to the implicit complexities associated with it. The performance of a recognition system is immensely dependent on extracted features. There are various features extraction approaches proposed in recent years. Among many, an approach based on zoning features proved to be efficient and popular. Such zoning features represent significant information with low complexity and high speed. In this paper, we used zoning features for the classification of Urdu Nasta'liq text lines, with a combination of 2-Dimensional Long Short Term Memory networks (2DLSTM) as learning classifier. The proposed model is evaluated on publicly available UPTI dataset and character recognition rate of 93.39% is obtained.
Notes Published in the journal Procedia Computer Science, vol 96, pp.16-22
ISSN 1877-0509
Language eng
DOI 10.1016/j.procs.2016.08.084
Indigenous content off
Field of Research 08 Information and Computing Sciences
10 Technology
HERDC Research category E1.1 Full written paper - refereed
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30132590

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.