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Manipuri Handwritten Character Recognition by Convolutional Neural Network

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Computer Vision and Image Processing (CVIP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1148))

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Abstract

Handwritten character recognition is an essential field in pattern recognition. Its popularity is increasing with the potential to thrive in various applications such as banking, postal automation, form filling, etc. However, developing such a system is a challenging task with the diverse writing style of the same character, and present of visually similar characteristics. In this paper, a recognition system is proposed using a deep neural network. The performance of the network is investigated on a self-collected handwritten dataset of Manipuri script contributed by 90 different people of varying age and education. A total of 4900 sample images is considered for the experiment and recorded a recognition rate of 98.86%.

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Author information

Authors and Affiliations

  1. National Institue of Technology, Manipur, Imphal, India

    Sanasam Inunganbi & Khumanthem Manglem

  2. National Institute of Technology, Hamirpur, Himachal Pradesh, India

    Prakash Choudhary

Authors
  1. Sanasam Inunganbi
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  2. Prakash Choudhary
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  3. Khumanthem Manglem
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Corresponding author

Correspondence to Sanasam Inunganbi .

Editor information

Editors and Affiliations

  1. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Neeta Nain

  2. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Santosh Kumar Vipparthi

  3. Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

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Inunganbi, S., Choudhary, P., Manglem, K. (2020). Manipuri Handwritten Character Recognition by Convolutional Neural Network. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1148. Springer, Singapore. https://doi.org/10.1007/978-981-15-4018-9_28

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  • DOI: https://doi.org/10.1007/978-981-15-4018-9_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4017-2

  • Online ISBN: 978-981-15-4018-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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