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Bangla Handwritten City Name Recognition Using Gradient-Based Feature

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Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 515))

Abstract

In recent times, holistic word recognition has achieved enormous attention from the researchers due to its segmentation-free approach. In the present work, a holistic word recognition method is presented for the recognition of handwritten city names in Bangla script. At first, each word image is hypothetically segmented into equal number of grids. Then gradient-based features, inspired by Histogram of Oriented Gradients (HOG) feature descriptor, are extracted from each of the grids. For the selection of suitable classifier, five well-known classifiers are compared in terms of their recognition accuracies and finally the classifier Sequential Minimal Optimization (SMO) is chosen. The system has achieved 90.65% accuracy on 10,000 samples comprising of 20 most popular city names of West Bengal, a state of India.

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References

  1. Chaudhuri, B.B., Pal, U.: A complete printed Bangla OCR system. Pattern Recognition. 31(5), 53–549(1998).

    Google Scholar 

  2. Basu, S., Das, N., Sarkar, R., Kundu, M., Nasipuri, M., Basu, D.K.: A hierarchical approach to recognition of handwritten Bangla characters. Pattern Recognition, 42(7), 1467–1484(2009).

    Google Scholar 

  3. Bhowmik, S., Polley, S., Roushan, M.G., Malakar, S., Sarkar, R., Nasipuri, M.: A holistic word recognition technique for handwritten Bangla words. International Journal Applied Pattern Recognition, 2(2), 142–159(2015).

    Google Scholar 

  4. Malakar, S., Ghosh, P., Sarkar, R., Das, N., Basu, S., Nasipuri, M.: An improved offline handwritten character segmentation algorithm for Bangla script. In: 5th Indian International Conference on Artificial Intelligence (IICAI-11), 71–90(2011).

    Google Scholar 

  5. Lavrenko, V., Rath, T.M., Manmatha, R.: Holistic word recognition for handwritten historical documents. In:Proceedings of First International Workshop on Document Image Analysis for Libraries,278–287, IEEE(2004).

    Google Scholar 

  6. Ishidera, E., Lucas, S.M., Downton, A.C.: Top-Down Likelihood Word Image Generation Model for Holistic Word Recognition. In: Proceedings of the 5th International Workshop on Document Analysis Systems V, 82–94, Springer-Verlag(2002).

    Google Scholar 

  7. Bhowmik, S., Malakar, S., Sarkar, R., Nasipuri, M.: Handwritten Bangla Word Recognition Using Elliptical Features. In: International Conference on Computational Intelligence and Communication Networks (CICN), 257–261, IEEE(2014).

    Google Scholar 

  8. Bhowmik, S., Roushan, M. G., Sarkar, R., Nasipuri, M., Polley, S., Malakar, S.: Handwritten Bangla Word Recognition Using HOG Descriptor. In:Fourth International Conference of Emerging Applications of Information Technology (EAIT), 193–197, IEEE (2014).

    Google Scholar 

  9. Acharyya, A., Rakshit, S., Sarkar, R., Basu, S., Nasipuri, M.. Handwritten Word Recognition Using MLP based Classifier: A Holistic Approach. International Journal of Computer Science Issues, 10(2), 422–427(2013).

    Google Scholar 

  10. Shaw, B., Parui, S.K., Shridhar, M.: Offline Handwritten Devanagari Word Recognition: A holistic approach based on directional chain code feature and HMM. In:International Conference onInformation Technology, 203–208, IEEE(2008).

    Google Scholar 

  11. Singh, B., Mittal, A., Ansari, M.A., Ghosh, D.: Handwritten Devanagari Word Recognition: A Curvelet Transform Based Approach. International Journal on Computer Science and Engineering, 3(4), 1658–1665(2011).

    Google Scholar 

  12. Dehghan, M., Faez, K., Ahmadi, M., Shridhar, M.: Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMM. Pattern Recognition, 34(5), 1057–1065(2001).

    Google Scholar 

  13. 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. International Journal on Document Analysis and Recognition, 15(1), 71–83(2012).

    Google Scholar 

  14. Dalal, N.,Triggs, B.: Histograms of oriented gradients for human detection. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR),1, pp. 886–893, IEEE (2005).

    Google Scholar 

  15. List of cities in West Bengal by population: https://en.wikipedia.org/wiki/List_of_cities_in_West_Bengal_by_population

  16. Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics, 9,62–66 (1979).

    Google Scholar 

  17. Gonzalez, R.C.: Digital Image Processing. Pearson Education, India(2009).

    Google Scholar 

  18. M. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, Ian H.: The WEKA Data Mining Software: An Update; SIGKDD Explorations, 11(1)(2009).

    Google Scholar 

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Authors and Affiliations

  1. Jadavpur University, Kolkata, India

    Shilpi Barua, Showmik Bhowmik, Ram Sarkar & Mita Nasipuri

  2. MCKV Institute of Engineering, Howrah, India

    Samir Malakar

Authors
  1. Shilpi Barua
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  2. Samir Malakar
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  3. Showmik Bhowmik
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  4. Ram Sarkar
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  5. Mita Nasipuri
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Corresponding author

Correspondence to Shilpi Barua .

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Editors and Affiliations

  1. ANITS, Prof., Comp. Sci. & Engg. Dept. ANITS, Visakhapatnam, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Dept. of ECE, Shri Ramswaroop Mem. Group of Prof. Clg Dept. of ECE, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. SCIS, University of Hyderabad , Hyderabad, India

    Siba K. Udgata

  4. KIIT University, School of Computer Engineering KIIT University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

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Barua, S., Malakar, S., Bhowmik, S., Sarkar, R., Nasipuri, M. (2017). Bangla Handwritten City Name Recognition Using Gradient-Based Feature. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_34

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  • DOI: https://doi.org/10.1007/978-981-10-3153-3_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3152-6

  • Online ISBN: 978-981-10-3153-3

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