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Handwritten Indic Script Identification from Document Images—A Statistical Comparison of Different Attribute Selection Techniques in Multi-classifier Environment

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Proceedings of the Second International Conference on Computer and Communication Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 381))

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Abstract

Script identification from document images is an essential task before choosing script-specific OCR for a Multi-lingual/Multi-script country like India. The problem becomes more complex when handwritten document images are considered. Several techniques have been developed so far for HSI (Handwritten Script Identification) problem and the work is still in progress. But the issue of dimensionality reduction of the feature set for script identification problem has not been addressed in the literature till date. This paper presents a statistical performance analysis of different attribute selection techniques in a multi-classifier environment for HSI problem on Indic scripts. A GAS (Greedy Attribute Selection) technique for HSI problem has also been proposed here. Encouraging outcomes are found observing the complexities of handwritten Indic scripts.

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References

  1. Obaidullah, S.M., Das, S.K., Roy, K.: A system for handwritten script identification from indian document. J. Pattern Recognit. Res. 8(1), 1–12 (2013)

    Article  Google Scholar 

  2. Ghosh, D., Dube, T., Shivprasad, S.P.: Script recognition—a review. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2142–2161 (2010)

    Article  Google Scholar 

  3. Chaudhuri, B.B., Pal, U.: A complete printed Bangla OCR. Pattern Recogn. 31, 531–549 (1998)

    Article  Google Scholar 

  4. Pal, U., Chaudhuri, B.B.: Identification of different script lines from multi-script documents. Image Vis. Comput. 20(13-14), 945–954 (2002)

    Article  Google Scholar 

  5. Hochberg, J., Kelly, P., Thomas, T., Kerns, L.: Automatic script identification from document images using cluster-based templates. IEEE Trans. Pattern Anal. Mach. Intell. 19, 176–181 (1997)

    Google Scholar 

  6. Chaudhury, S., Harit, G., Madnani, S., Shet, R.B.: Identification of scripts of Indian languages by combining trainable classifiers. In: Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing, Bangalore, India, Dec-20–22 2000

    Google Scholar 

  7. Dhanya, D., Ramakrishnan, A.G., Pati, P.B.: Script identification in printed bilingual documents. In: Sadhana, vol. 27, part-1, pp. 73–82 (2002)

    Google Scholar 

  8. Pati, P.B., Ramakrishnan, A.G.: Word level multi-script identification. Pattern Recogn. Lett. 29(9), 1218–1229 (2008)

    Article  Google Scholar 

  9. Obaidullah, S.M., Mondal, A., Das, N., Roy, K.: Script Identification from printed indian document images and performance evaluation using different classifiers. Appl. Comput. Intell. Soft Comput, vol. 2014, p. 12. Article ID 896128 (2014). doi:10.1155/2014/896128

    Google Scholar 

  10. Roy, K., Banerjee, A., Pal, U.: A system for word-wise handwritten script identification for indian postal automation. In: Proceedings of IEEE India Annual Conference 2004, pp. 266-271 (2004)

    Google Scholar 

  11. Vajda, S., Roy, K., Pal, U., Chaudhuri, B.B., Belaid, A.: Automation of Indian postal documents written in Bangla and English. Int. J. Pattern Recognit. Artif. Intell. 23(8), 1599–1632 (2009)

    Article  Google Scholar 

  12. http://www.mathworks.in/help/pdf_doc/images/images_tb.pdf. Accessed 01 Feb 2015

  13. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. 11, 10–18 (2009)

    Article  Google Scholar 

  14. http://www.scholarpedia.org/article/Evolution_strategies. Accessed 01 March 2015

  15. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Boston (1989)

    Google Scholar 

  16. Guetlein, M., Frank, E. Hall, M., Karwath, A.: Large scale attribute selection using wrappers. In: Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, pp. 332–339 (2009)

    Google Scholar 

  17. Moraglio, A., Chio, D., Poli, C.R.: Geometric particle swarm optimization. In: Proceedings of the 10th European Conference on Genetic Programming, Berlin, Heidelberg, pp. 125–136 (2007)

    Google Scholar 

  18. Hall, M., Holmes, G.: Benchmarking attribute selection techniques for discrete class data mining. IEEE Trans. Knowl. Data Eng. 15(6), 1437–1447 (2003)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Aliah University, Kolkata, W.B, India

    Sk Md Obaidullah

  2. Department of Computer Science, West Bengal State University, Barasat, W.B, India

    Chayan Halder & Kaushik Roy

  3. Department of Computer Science and Engineering, Jadavpur University, Kolkata, W.B, India

    Nibaran Das

Authors
  1. Sk Md Obaidullah
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  2. Chayan Halder
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  3. Nibaran Das
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  4. Kaushik Roy
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Corresponding author

Correspondence to Sk Md Obaidullah .

Editor information

Editors and Affiliations

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

    Suresh Chandra Satapathy

  2. Department of CSE, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

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

    Vikrant Bhateja

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Obaidullah, S.M., Halder, C., Das, N., Roy, K. (2016). Handwritten Indic Script Identification from Document Images—A Statistical Comparison of Different Attribute Selection Techniques in Multi-classifier Environment. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 381. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2526-3_51

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  • DOI: https://doi.org/10.1007/978-81-322-2526-3_51

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2525-6

  • Online ISBN: 978-81-322-2526-3

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