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ShonkhaNet: A Dynamic Routing for Bangla Handwritten Digit Recognition Using Capsule Network

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1037))

  • The original version of this chapter was revised: The names of the two Authors have been corrected as “AKM Shahariar Azad Rabby” and “Syed Akhter Hossain”. The correction to this chapter is available at https://doi.org/10.1007/978-981-13-9187-3_67

Abstract

In the present world, one of the most interesting topics is Handwritten Recognition due to its academic and commercial interest in different research fields. But deal with it a little bit tough because of different size and style. There are many works have been accomplished base in handwritten recognition including Bangla. Here proposed a model which is classified Bangla handwritten numeral using capsule net (a new type of neural network represents activity vector as parameters). The Model is trained and valid with ISI handwritten database [1], BanglaLekha Isolated [2], CMATERdb 3.1.1 [3] and all database together that was achieved 99.28% validation accuracy on ISI handwritten character database, 97.62% validation accuracy on BanglaLekha Isolated, 98.33% validation accuracy on CMATERdb 3.1.1 dataset and 98.90% validation accuracy combination mixed dataset. This model gives satisfactory recognition accuracy compared to other existing models.

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Change history

  • 17 August 2019

    In the originally published version, the names of the two Authors on pages 108, 149, and 159 were incorrect. The names have been corrected as “AKM Shahariar Azad Rabby” and “Syed Akhter Hossain”.

References

  1. Bhattacharya, U., Chaudhuri, B.: Handwritten numeral databases of Indian scripts and multistage recognition of mixed numerals. IEEE Trans. Pattern Anal. Mach. Intell. 31, 444–457 (2009). https://doi.org/10.1109/TPAMI.2008.88

    Article  Google Scholar 

  2. Biswas, M., et al.: BanglaLekhaIsolated: a multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters. Data in Brief 12, 103–107 (2017). https://doi.org/10.1016/j.dib.2017.03.035

    Article  Google Scholar 

  3. Sarkar, R., Das, N., Basu, S., Kundu, M., Nasipuri, M., Basu, D.K.: CMATERdb1: a database of unconstrained handwritten Bangla and Bangla-English mixed script document image. Int. J. Doc. Anal. Recogn. (IJDAR) 15(1), 71–83 (2012)

    Article  Google Scholar 

  4. Cheriet, M., Yacoubi, M.E., Fujisawa, H., Lopresti, D., Lorette, G.: Handwritten recognition research: Twenty years of achievement... and beyond. Pattern Recogn. 42, 3131–3135 (2009)

    Article  Google Scholar 

  5. Dong, J., Krzyżak, A., Suen, C.Y.: An improved handwritten Chinese character recognition system using support vector machine. Pattern Recogn. Lett. 26(12), 1849–1856 (2005)

    Article  Google Scholar 

  6. Zhu, B., Zhou, X.-D., Liu, C.-L., Nakagawa, M.: A robust model for on-line handwritten Japanese text recognition. IJDAR 13(2), 121–131 (2010)

    Article  Google Scholar 

  7. Kim, H.J., Kim, P.K.: Recognition of off-line handwritten Korean characters. Pattern Recogn. 29, 245–254 (1996)

    Article  Google Scholar 

  8. Geoffrey, E.H., et al.: Dynamic Routing Between Capsules. 1710.09829v2 [cs.CV], 7 November 2017

    Google Scholar 

  9. Hinton, G.E., Krizhevsky, A., Wang, S.D.: Transforming auto-encoders. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds.) ICANN 2011. LNCS, vol. 6791, pp. 44–51. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21735-7_6

    Chapter  Google Scholar 

  10. Pal, U., Chaudhuri, B.B.: Automatic recognition of unconstrained off-line Bangla handwritten numerals. In: Tan, T., Shi, Y., Gao, W. (eds.) ICMI 2000. LNCS, vol. 1948, pp. 371–378. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-40063-X_49

    Chapter  Google Scholar 

  11. Alom, M.Z., Sidike, P., Taha, T.M., Asari, V.: Handwritten Bangla Digit Recognition Using Deep Learning (2017)

    Google Scholar 

  12. Rabby, A.K.M.S.A., Abujar, S., Haque, S., Hossain, S.A.: Bangla handwritten digit recognition using convolutional neural network. In: Abraham, A., Dutta, P., Mandal, J.K., Bhattacharya, A., Dutta, S. (eds.) Emerging Technologies in Data Mining and Information Security. AISC, vol. 755, pp. 111–122. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-1951-8_11

    Chapter  Google Scholar 

  13. Kingma, D.P., Ba, J.: Adam: A Method for Stochastic Optimization. arXiv:1412.6980 [cs.LG], December 2014

  14. Janocha, K., Czarnecki, M.W.: On loss functions for deep neural networks in classification. arxiv, abs/1702.05659 (2017)

    Google Scholar 

  15. Khan, H.A., Al Helal, A., Ahmed, K.I.: Handwritten Bangla digit recognition using sparse representation classifier. In: 2014 International Conference on Informatics, Electronics & Vision (ICIEV), pp. 1–6. IEEE (2014)

    Google Scholar 

  16. Wen, Y., He, L.: A classifier for Bangla handwritten numeral recognition. Expert Syst. Appl. 39(1), 948–953 (2012)

    Article  Google Scholar 

  17. Nasir, M.K., Uddin, M.S.: Handwritten Bangla numerals recognition for automated postal system. IOSR J. Comput. Eng. 8(6), 43–48 (2013)

    Article  Google Scholar 

  18. Islam, S., Shill, P.C., Rahman, M.M., Akhand, M.A.H., Rahman, M.M.H.: Bangla handwritten character recognition using convolutional neural network. Int. J. Image Graphics Signal Process. (IJIGSP) 73, 42–49 (2015)

    Google Scholar 

  19. Sarkhel, R., Das, N., Saha, A.K., Nasipuri, M.: A multi-objective approach towards cost-effective isolated handwritten Bangla character and digit recognition. Pattern Recogn. 58, 172–189 (2016)

    Article  Google Scholar 

  20. Basu, S., Sarkar, R., Das, N., Kundu, M., Nasipuri, M., Basu, D.K.: Handwritten Bangla digit recognition using classifier combination through DS Technique. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds.) PReMI 2005. LNCS, vol. 3776, pp. 236–241. Springer, Heidelberg (2005). https://doi.org/10.1007/11590316_32

    Chapter  Google Scholar 

  21. Santosh, K.C., Wendling, L.: Character recognition based on non-linear multi-projection profiles measure. Front. Comput. Sci. 9, 678–690 (2015)

    Article  Google Scholar 

  22. Deans, S.R.: Applications of the Radon Transform. Wiley Interscience Publications, New York (1983)

    MATH  Google Scholar 

  23. Santosh, K.C.: Character recognition based on DTW-radon. In: 2011 International Conference on Document Analysis and Recognition. IEEE (2011)

    Google Scholar 

  24. Kruskall, J.B., Liberman, M.: The symmetric time warping algorithm: From continuous to discrete. In: Time Warps, String Edits and Macromolecules: The Theory and Practice of String Comparison, pp. 125–161. Addison-Wesley, Boston (1983)

    Google Scholar 

  25. Hassan, T., Khan, H.A.: Handwritten bangla numeral recognition using local binary pattern. In: 2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), pp. 1–4. IEEE (2015)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Daffodil International University, Dhanmondi, Dhaka, 1205, Bangladesh

    Sadeka Haque, AKM Shahariar Azad Rabby, Md. Sanzidul Islam & Syed Akhter Hossain

Authors
  1. Sadeka Haque
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  2. AKM Shahariar Azad Rabby
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  3. Md. Sanzidul Islam
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  4. Syed Akhter Hossain
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Corresponding authors

Correspondence to Sadeka Haque or AKM Shahariar Azad Rabby .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Haque, S., Rabby, A.S.A., Islam, M.S., Hossain, S.A. (2019). ShonkhaNet: A Dynamic Routing for Bangla Handwritten Digit Recognition Using Capsule Network. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_15

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  • DOI: https://doi.org/10.1007/978-981-13-9187-3_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9186-6

  • Online ISBN: 978-981-13-9187-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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