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Frontiers in Intelligent Computing: Theory and Applications pp 69–77Cite as

Deep Convolutional Neural Networks for Recognition of Historical Handwritten Kannada Characters

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1014))

Abstract

Handwritten character recognition is an important step toward automatic transliteration of the valuable historical documents archived in digital libraries. This is a challenging task as it requires a labor-intensive handcrafting of features from a huge set of character classes. Moreover, the intra-class variability of handwritten characters is high causing a major bottleneck for recognition accuracy. A deep convolutional neural networks (DCNN) approach for character recognition of handwritten historical Kannada manuscripts is presented in this paper. DCNN is a model that unifies feature extraction and classification. It inherently learns the most discriminative features from the given data, thus subverting the usage of handcrafted features. In this work, the features extracted from the characters using DCNN are fed to SGDM and SVM classification algorithms for recognition. This approach is experimented on the digitized estampages of historical Kannada stone inscriptions belonging to eleventh century and promising results are observed.

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Acknowledgements

We thank the officials of Archaeological Survey of India (ASI), Mysore for permitting us to use the eleventh-century estampages of historical Kannada stone inscriptions from their archives for our research.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Visveswaraya Technological University, Belagavi, India

    H. T. Chandrakala

  2. Department of Computer Science and Engineering, BMS Institute of Technology & Management, Bengaluru, India

    G. Thippeswamy

Authors
  1. H. T. Chandrakala
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  2. G. Thippeswamy
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Corresponding author

Correspondence to H. T. Chandrakala .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, SRMGPC, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Duy Tan University, Da Nang, Vietnam

    Bao Le Nguyen

  4. Graduate School, Duy Tan University, Da Nang, Vietnam

    Nhu Gia Nguyen

  5. Faculty of Information Technology, Hai Phong University, Hai Phong, Vietnam

    Dac-Nhuong Le

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Chandrakala, H.T., Thippeswamy, G. (2020). Deep Convolutional Neural Networks for Recognition of Historical Handwritten Kannada Characters. In: Satapathy, S., Bhateja, V., Nguyen, B., Nguyen, N., Le, DN. (eds) Frontiers in Intelligent Computing: Theory and Applications. Advances in Intelligent Systems and Computing, vol 1014. Springer, Singapore. https://doi.org/10.1007/978-981-13-9920-6_7

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