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Information Systems Design and Intelligent Applications pp 285–293Cite as

Line-Level Script Identification for Six Handwritten Scripts Using Texture Based Features

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 340))

Abstract

Script identification from a given document image has some important applicability in many computer applications such as automatic archiving of multilingual documents, searching online archives of document images and for the selection of script specific Optical Character Recognition (OCR) engine in any multilingual environment. In this paper, we propose a texture based approach for text line-level script identification of six handwritten scripts namely, Bangla, Devnagari, Malayalam, Tamil, Telugu and Roman. A set of 80 features based on Gray Level Co-occurrence Matrix (GLCM) has been designed for the present work. Multi Layer Perceptron (MLP) is found to be the best classifier among a set of popular multiple classifiers which is then extensively tested by tuning different parameters. Finally, an accuracy of 95.67 % has been achieved on a dataset of 600 text lines using 3-fold cross validation with epoch size 1,500 of MLP classifier.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Pawan Kumar Singh, Ram Sarkar & Mita Nasipuri

Authors
  1. Pawan Kumar Singh
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  2. Ram Sarkar
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  3. Mita Nasipuri
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Corresponding author

Correspondence to Pawan Kumar Singh .

Editor information

Editors and Affiliations

  1. University of Kalyanai, Kalyanai, West Bengal, India

    J. K. Mandal

  2. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  3. Dean, Faculty of Engineering, Technology, University of Kalyani, Kalyani, West Bengal, India

    Manas Kumar Sanyal

  4. Engineering and Technological Studies, University of Kalyani, Kalyani, West Bengal, India

    Partha Pratim Sarkar

  5. Department Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Anirban Mukhopadhyay

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Singh, P.K., Sarkar, R., Nasipuri, M. (2015). Line-Level Script Identification for Six Handwritten Scripts Using Texture Based Features. In: Mandal, J., Satapathy, S., Kumar Sanyal, M., Sarkar, P., Mukhopadhyay, A. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 340. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2247-7_30

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  • DOI: https://doi.org/10.1007/978-81-322-2247-7_30

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2246-0

  • Online ISBN: 978-81-322-2247-7

  • eBook Packages: EngineeringEngineering (R0)

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