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Restoration of Degraded Historical Kannada Handwritten Document Images Using Image Enhancement Techniques

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Book cover Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) (SoCPaR 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 614))

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Abstract

The digital image processing has got much attention of the researchers towards development of automatic optical character recognition system. The document image analysis mainly focused on printed and handwritten document images. In printed document image analysis, the input image is that of machine printed document, where as in handwritten document image analysis, it is of document, handwritten by different persons on a paper by using pen or pencil. Presently, most of the research work addresses issues related to handwritten document images and the Kannada script. The printed script recognition system is much easier than handwritten script recognition system. In printed documents, font style and size of the characters are standardized, where as handwritten characters vary in size and style of font from person to person and time to time, which is a very tedious job for recognition. In this paper, a new novel approach is proposed for restoration of degraded historical Kannada handwritten documents using the combination of special local and global binarization techniques, by eliminating of non-uniformly illuminated background. The performance evaluation is done by extracting geometric feature values of Pricision, Recall, F-Measure, MSE and PSNR and these results are compared with manual results obtained by the Epigraphists. It is also compared with other standard methods, namely, souvola and niblack in the literature, which demonstrate the efficacy of the proposed method. Restoration of degraded historical Kannada handwritten documents plays an important role in age identification, Kannada character recognition and classification for the Kannada handwritten documents.

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Acknowledgments

The authors are indebted to The Chairman, Department of P.G. Studies and Research in Kannada, Gulbarga University, Kalaburgi, for providing degraded Kannada handwritten document images and visualizing the computed results. The authors are also grateful to Bickley diary and H-DIBCO series datasets.

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Authors and Affiliations

  1. Department of Computer Science, Rani Channamma University, Belagavi, 591156, Karnataka, India

    Parashuram Bannigidad & Chandrashekar Gudada

Authors
  1. Parashuram Bannigidad
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  2. Chandrashekar Gudada
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Corresponding author

Correspondence to Chandrashekar Gudada .

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Editors and Affiliations

  1. Scientific Network for Innovation and Research, Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA

    Ajith Abraham

  2. VIT University, Vellore, Tamil Nadu, India

    Aswani Kumar Cherukuri

  3. School of Engineering, Polytechnic of Porto (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  4. Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Bannigidad, P., Gudada, C. (2018). Restoration of Degraded Historical Kannada Handwritten Document Images Using Image Enhancement Techniques. In: Abraham, A., Cherukuri, A., Madureira, A., Muda, A. (eds) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016). SoCPaR 2016. Advances in Intelligent Systems and Computing, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-60618-7_49

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  • DOI: https://doi.org/10.1007/978-3-319-60618-7_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60617-0

  • Online ISBN: 978-3-319-60618-7

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