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Assamese Character Recognition Using Zoning Feature

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Advances in Electronics, Communication and Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 443))

Abstract

The aim of this paper is to develop a model to recognize basic Assamese characters using feed-forward neural network. The basic characters included in Assamese language are a set of numeral, a set of vowel, and a set of consonant. An algorithm has been designed to segment the line and individual character of the image and zoning features are extracted from the individual character. The network is trained by gradient descent with momentum and adaptive learning rate backpropagation training function. The network consists of two hidden layers with Sum Square Error (SSE). Finally, the unicode value of the recognized character is written in a text file.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Gauhati University, Guwahati, India

    Kalyanbrat Medhi & Sanjib Kr. Kalita

Authors
  1. Kalyanbrat Medhi
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  2. Sanjib Kr. Kalita
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Corresponding author

Correspondence to Kalyanbrat Medhi .

Editor information

Editors and Affiliations

  1. Smart Energy Research Unit, College of Engineering and Science, Victoria University, Melbourne, VIC, Australia

    Akhtar Kalam

  2. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  3. Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Rangpo, Sikkim, India

    Kalpana Sharma

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Medhi, K., Kalita, S.K. (2018). Assamese Character Recognition Using Zoning Feature. In: Kalam, A., Das, S., Sharma, K. (eds) Advances in Electronics, Communication and Computing. Lecture Notes in Electrical Engineering, vol 443. Springer, Singapore. https://doi.org/10.1007/978-981-10-4765-7_39

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  • DOI: https://doi.org/10.1007/978-981-10-4765-7_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4764-0

  • Online ISBN: 978-981-10-4765-7

  • eBook Packages: EngineeringEngineering (R0)

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