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Handwritten Oriya Digit Recognition Using Maximum Common Subgraph Based Similarity Measures

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Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 435))

Abstract

Optical Character Recognition have attracted the attention of lots of researchers lately. In the current work we propose a graph based approach to perform a recognition task for handwritten Oriya digits. Our proposal includes a procedure to convert handwritten digits into graphs followed by computation of the maximum common subgraph. Finally similarity measures between graphs were used to design a feature vector. Classification was performed using the K-nearest neighbor algorithm. After training the system on 5000 images an accuracy of 97.64 % was achieved on a test set of 2200 images. The result obtained shows the robustness of our approach.

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References

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Author information

Authors and Affiliations

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

    Swarnendu Ghosh, Nibaran Das, Mahantapas Kundu & Mita Nasipuri

Authors
  1. Swarnendu Ghosh
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  2. Nibaran Das
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  3. Mahantapas Kundu
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  4. Mita Nasipuri
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Corresponding author

Correspondence to Swarnendu Ghosh .

Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  3. University of Hyderabad, Hyderabad, India

    Siba K. Udgata

  4. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Ghosh, S., Das, N., Kundu, M., Nasipuri, M. (2016). Handwritten Oriya Digit Recognition Using Maximum Common Subgraph Based Similarity Measures. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 435. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2757-1_18

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  • DOI: https://doi.org/10.1007/978-81-322-2757-1_18

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2756-4

  • Online ISBN: 978-81-322-2757-1

  • eBook Packages: EngineeringEngineering (R0)

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