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Proceedings of International Conference on Computer Vision and Image Processing pp 523–530Cite as

Study of Zone-Based Feature for Online Handwritten Signature Recognition and Verification in Devanagari Script

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 460))

Abstract

This paper presents one zone-based feature extraction approach for online handwritten signature recognition and verification of one of the major Indic scripts–Devanagari. To the best of our knowledge no work is available for signature recognition and verification in Indic scripts. Here, the entire online image is divided into a number of local zones. In this approach, named Zone wise Slopes of Dominant Points (ZSDP), the dominant points are detected first from each stroke and next the slope angles between consecutive dominant points are calculated and features are extracted in these local zones. Next, these features are supplied to two different classifiers; Hidden Markov Model (HMM) and Support Vector Machine (SVM) for recognition and verification of signatures. An exhaustive experiment in a large dataset is performed using this zone-based feature on original and forged signatures in Devanagari script and encouraging results are found.

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References

  1. W. Nelson, E. Kishon, “Use of Dynamic Features for Signature Verification”, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1991, Charlottesville, USA, pp. 201–205.

    Google Scholar 

  2. R. Ghosh, P.P. Roy, “Study of two zone based features for online Bengali and Devanagari character recognition”, Proceedings of the 13th International Conference on Document Analysis and Recognition (ICDAR), 2015, Nancy, France, pp. 401–405.

    Google Scholar 

  3. R. Plamondon, G. Lorette, “Automatic signature verification and writer identification- the state of the art”, Pattern Recognition, 1989, Vol. 22, Issue 2, pp. 107–131.

    Google Scholar 

  4. M. Parezeau, R. Plamendon, “A Comparative Analysis of Regional Correlation, Dynamic Time Warping and Skeleton Matching for Signature Verification”, IEEE Transaction on Pattern Recognition and Machine Intelligence, 1990, Vol. 12, Issue 7, pp. 710–717.

    Google Scholar 

  5. Y. Sato, K. Kogure, “Online signature verification based on shape, motion and writing”, Proceedings of the 6th International Conference on Pattern Recognition, 1982, Munich, Germany, pp. 823–826.

    Google Scholar 

  6. P. Zhao, A. Higashi, Y. Sato, “On-line signature verification by adaptively weighted DP matching”, IEICE Transaction on Information System, 1996, Vol. E79-D, Issue 5, pp. 535–541.

    Google Scholar 

  7. W.T. Nelson, W. Turin, T. Hastie, “Statistical Methods for On-Line Signature Verification”, International Journal of Pattern Recognition and Artificial Intelligence, 1994, Vol. 8, Issue 3, pp. 749–770.

    Google Scholar 

  8. L.L. Lee, T. Berger, E. Aviczer, “Reliable On-Line Signature Verification Systems”, IEEE Transaction on Pattern Analysis and Machine Intelligence, 1996, Vol. 18, Issue 6, pp. 643–649.

    Google Scholar 

  9. D. Letjman, S. Geoge, “On-Line Handwritten Signature Verification Using Wavelet and Back Propagation Neural Networks”, Proceedings of the 6th International Conference on Document Analysis and Recognition (ICDAR), 2001, Seattle, USA, pp. 596–598.

    Google Scholar 

  10. Q.Z. Wu, S.Y. Lee, I.C. Jou, “On-Line Signature Verification Based on Logarithmic Spectrum”, Pattern Recognition, 1998, Vol. 31, Issue 12, pp. 1865–1871.

    Google Scholar 

  11. G. Dimauro, G. Impedevo, G. Pirlo, “Component Oriented Algorithms for Signature Verification”, International Journal of Pattern Recognition and Artificial Intelligence, 1994, Vol. 8, Issue 3, pp. 771–794.

    Google Scholar 

  12. J.F. Aguilar, S. Krawczyk, J.O. Garcia, A.K. Jain, “Fusion of Local and Regional Approaches for On-Line Signature Verification”, Proceedings of the International Workshop on Biometric Recognition System, 2005, Beijing, China, pp. 188–196.

    Google Scholar 

  13. S. Jaeger, S. Manke, J. Reichert, A. Waibel, “Online handwriting recognition: The NPen++ recognizer,” International Journal on Document Analysis and Recognition, 2001, Volume 3, Issue 3, pp. 169–180.

    Google Scholar 

  14. C. Burges, “A tutorial on support vector machines for pattern recognition”, Data Mining and Knowledge Discovery, vol.2, pp. 1–43.

    Google Scholar 

  15. U. Pal, P. P. Roy, N. Tripathy, J. Lladós, “Multi-Oriented Bangla and Devanagari Text Recognition”, Pattern Recognition, vol. 43, 2010, pp. 4124–4136.

    Google Scholar 

  16. P.P. Roy, P. Dey, S. Roy, U. Pal, F. Kimura, “A Novel Approach of Bangla Handwritten Text Recognition using HMM”, Proceedings of the 14th International Conference on Frontiers in Handwriting Recognition, 2014, Heraklion, Greece, pp. 661–666.

    Google Scholar 

  17. S. Young. The HTK Book, Version 3.4. Cambridge Univ. Eng. Dept., 2006.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, National Institute of Technology, Patna, India

    Rajib Ghosh

  2. Department of Computer Science & Engineering, Indian Institute of Technology, Roorkee, India

    Partha Pratim Roy

Authors
  1. Rajib Ghosh
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  2. Partha Pratim Roy
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Corresponding author

Correspondence to Rajib Ghosh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Sanjeev Kumar

  3. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Partha Pratim Roy

  4. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Debashis Sen

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Ghosh, R., Roy, P.P. (2017). Study of Zone-Based Feature for Online Handwritten Signature Recognition and Verification in Devanagari Script. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_47

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  • DOI: https://doi.org/10.1007/978-981-10-2107-7_47

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2106-0

  • Online ISBN: 978-981-10-2107-7

  • eBook Packages: EngineeringEngineering (R0)

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