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Computing, Communication and Signal Processing pp 1001–1010Cite as

Age-Type Identification and Recognition of Historical Kannada Handwritten Document Images Using HOG Feature Descriptors

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 810))

Abstract

Most of the historical Kannada handwritten documents are preserved in the manuscript preservation centre and archaeological departments. The historical Kannada handwritten documents are generally degraded in nature, due to this degradation, the documents are impossible to read and understand the contents. Hence, it is very much essential to restore by digitizing the historical Kannada handwritten documents and also recognize the originality of the dynasty to which it belongs. The main objective of the research work is to reconstruct, digitize and recognize the historical Kannada handwritten document images by applying image enhancement techniques and obtain the HOG feature descriptors using K-nearest neighbour (K-NN) and SVM classifiers. In this paper, we have considered historical Kannada handwritten document images of different dynasties based on their age-type; Vijayanagara dynasty (1460 AD), Mysore Wadiyar dynasty (1936 AD), Vijayanagara dynasty (1400 AD) and Hoysala dynasty (1340 AD) for experimentation. The average classification accuracy for different dynasties: in case of K-NN classifier is 92.3% and SVM classifier is 96.7%, It is observed that the SVM classifier has got a good classification performance comparatively K-NN classifier for Historical Kannada handwritten document images. The experimental outcomes are tested with manual results and other methods in the literature, which show the thoroughness of the proposed technique.

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References

  1. Manjunath, M.G., Devarajaswamy, G.K., Vikasa, K.L.: Jagadhguru Sri Madhvacharya Trust, Sri Raghavendra Swami Matta, Mantralaya

    Google Scholar 

  2. Narasimha Murthy, A.V.: Kannada Lipiya Ugama Mattu Vikasa, Kannada Adhyayana Samsthe, Mysore University, Mysore (1968)

    Google Scholar 

  3. Reddy, D.: Lipiya Huttu Mattu Belavanige—Origin and Evolution of Script, Kannada Pustaka Pradhikara (Kannada Book Authority), Bangalore

    Google Scholar 

  4. Lavrenko, V., Rath, T.M., Manmath, R.: Holistic word recognition for handwritten documents. In: Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL’04), pp. 278–287 (2004)

    Google Scholar 

  5. Sanchez, J.A., Bosch, V., Romero, V., Depuydt, K., de Does, J.: A Handwritten text recognition for historical documents in the tran Scriptorium Project. In: Proceedings of the First International Conference on Digital Access to Textual Cultural Heritage, DATeCH ‘14, pp. 111–117 (2014)

    Google Scholar 

  6. Dileep, D.: A feature extraction technique based on character geometry for character recognition. Comput. Res. Repos. J. 1202(3884), 1–4 (2012)

    Google Scholar 

  7. Romero, V., Serrano, N., Toselli, A.H., Sanchez, J.A., Vidal, E.: Handwritten text recognition for historical documents. In: Proceedings of Langauage Technologies for Digital heritage and Cultural Heritage Workshop, pp. 90–96

    Google Scholar 

  8. Gao, G., Su, X., Wei, H., Gong, Y.: Classical Mongolian words recognition in historical document. IEEE ICDAR 1520–5363(11), 692–697 (2011)

    Google Scholar 

  9. Soumya, A., Hemantha Kumar, G.: Performance analysis of random forests with SVM and KNN in classification of ancient Kannada scripts. Int. J. Comput. Technol. 13(9), pp. 4907–4921 (2014)

    Google Scholar 

  10. Gangamma, B., Murthy, K.S., Punitha, P.: Curvelet transform based approach for prediction of epigraphical scripts era. In: IEEE International Conference on Computational Intelligence and Computing Research, pp. 1–6 (2012) 978-4673-1344/12

    Google Scholar 

  11. Soumya, A., Hemantha Kumar, G.H.: SVM classifier for the predication of era of an epigraphical script. IJP2P 2(2), 12–22 (2011)

    Article  Google Scholar 

  12. Soumya, A., Hemantha Kumar, G.: Recognition of historical records using Gabor and zonal features. SIPIJ 6(4) 57–69 (2015)

    Google Scholar 

  13. Mohana, H.S., Navya, K., Srikanth, P.C., Shivakumar, G.: Stone inscripted Kannada Character matching Using SIFT. In: Proceedings of the IRF International Conference, pp. 126–131 (2014)

    Google Scholar 

  14. Verma, B., Blumenstein, M., Kulkarni, S.: Recent achievements in offline handwriting recognition system. In: International Conference on Computational Intelligence and Multimedia Applications (1998)

    Google Scholar 

  15. Bannigidad, P., Gudada, C.: Restoration of degraded historical Kannada handwritten document images using image enhancement techniques. In: International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016), pp. 498–508. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-60618-7_49

    Google Scholar 

  16. Bannigidad, P., Gudada, C.: Restoration of degraded Kannada handwritten paper inscriptions (Hastaprati) using image enhancement techniques. In: IEEE International Conference on Computer Communication and Informatics (ICCCI-2017), pp. 1–6 (2017) https://doi.org/10.1109/iccci.2017.8117697

  17. https://machinelearningmastery.com/k-nearest-neighbors-for-machine-learning/

  18. http://www.statsoft.com/Textbook/Support-Vector-Machines#Classification SVM

  19. https://en.wikipedia.org/wiki/Histogram_of_oriented_gradients

  20. Karthik, S., Srikanta Murthy, K.: Segmentation and recognition of handwritten kannada text using relevance feedback and histogram of oriented gradients—a novel approach. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 7(1), 472–476 (2016)

    Google Scholar 

  21. Alaei, A., Nagabhushan, P., Pal, U.: A benchmark Kannada handwritten document dataset and its segmentation. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 141–145 (2011)

    Google Scholar 

  22. Belagali, Netravati, Angadi, Shanmukhappa A.: OCR for handwritten Kannada language script. Int. J. Recent Trends Eng. Res. (IJRTER) 02(08), 190–197 (2016)

    Google Scholar 

  23. Sridharamurthy, S.K., Sudarshana Reddy, H.R.: PCA based feature for handwritten Kannada characters recognition. In: International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) (2015). https://doi.org/10.1109/erect.2015.7499053

  24. Manjunath Aradhya, V.N., Hemantha Kumar, G., Noushath, S.: Multilingual OCR system for South Indian scripts and English documents: an approach based on Fourier transform and principal component analysis. In: Engineering Applications of Artificial Intelligence Elsevier, vol. 21, no. 4, pp. 658–668 (2008)

    Article  Google Scholar 

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Acknowledgements

The authors are indebted to The Chairman, Department of P. G. Studies and Research in Kannada, Gulbarga University, Kalaburgi and Dept. of Hasataprati, Kannada University, Hampi for providing the historical Kannada handwritten documents and perception of manual outcomes.

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Authors and Affiliations

  1. Rani Channamma University, Belagavi, 591156, Karnataka, India

    Parashuram Bannigidad & Chandrashekar Gudada

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  1. Parashuram Bannigidad
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  2. Chandrashekar Gudada
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Correspondence to Chandrashekar Gudada .

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Editors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, Maharashtra, India

    Brijesh Iyer

  2. Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, Maharashtra, India

    S.L. Nalbalwar

  3. Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Nagendra Prasad Pathak

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Bannigidad, P., Gudada, C. (2019). Age-Type Identification and Recognition of Historical Kannada Handwritten Document Images Using HOG Feature Descriptors. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds) Computing, Communication and Signal Processing . Advances in Intelligent Systems and Computing, vol 810. Springer, Singapore. https://doi.org/10.1007/978-981-13-1513-8_101

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  • DOI: https://doi.org/10.1007/978-981-13-1513-8_101

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1512-1

  • Online ISBN: 978-981-13-1513-8

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