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Mobile signature verification: feature robustness and performance comparison

Mobile signature verification: feature robustness and performance comparison

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© The Institution of Engineering and Technology
Received 20/10/2013, Accepted 02/05/2014, Revised 01/05/2014, Published 06/06/2014

In this study, the effects of using handheld devices on the performance of automatic signature verification systems are studied. The authors compare the discriminative power of global and local signature features between mobile devices and pen tablets, which are the prevalent acquisition device in the research literature. Individual feature discriminant ratios and feature selection techniques are used for comparison. Experiments are conducted on standard signature benchmark databases (BioSecure database) and a state-of-the-art device (Samsung Galaxy Note). Results show a decrease in the feature discriminative power and a higher verification error rate on handheld devices. It is found that one of the main causes of performance degradation on handheld devices is the absence of pen-up trajectory information (i.e. data acquired when the pen tip is not in contact with the writing surface).

Inspec keywords: feature selection; mobile computing; handwriting recognition

Other keywords: feature selection techniques; performance comparison; handheld devices; automatic signature verification systems; feature robustness; global signature features; local signature features; mobile signature verification; pen-up trajectory information; prevalent acquisition device; standard signature benchmark databases

Subjects: Computer vision and image processing techniques; Image recognition; Ubiquitous and pervasive computing

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
      • 5. Fierrez, J., Ortega-Garcia, J.: ‘On-line signature verification’, in Jain, A.K., Ross, A., Flynn, P. (Eds.): ‘Handbook of biometrics’ (Springer, 2008), pp. 189–209.
    6. 6)
    7. 7)
      • 7. Martinez-Diaz, M., Fierrez, J., Ortega-Garcia, J.: ‘Universal background models for dynamic signature verification’. Proc. IEEE Conf. on Biometrics: Theory, Applications and Systems, BTAS, 2007, pp. 1–6.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
      • 14. Fierrez-Aguilar, J., Nanni, L., Lopez-Penalba, J., Ortega-Garcia, J., Maltoni, D.: ‘An on-line signature verification system based on fusion of local and global information’. Proc. IAPR Int. Conf. on Audio- and Video-Based Biometric Person Authentication, AVBPA, 2005(LNCS3546), pp. 523–532.
    15. 15)
    16. 16)
      • 16. Martinez-Diaz, M., Fierrez, J.: ‘Signature databases and evaluation’, in Li, S.Z. (Ed.): ‘Encyclopedia of biometrics’ (Springer, 2009), pp. 1178–1184.
    17. 17)
      • 17. Impedovo, D., Pirlo, G., Plamondon, R.: ‘Handwritten signature verification: new advancements and open issues’. Proc. Int. Conf. on Frontiers in Handwriting Recognition, ICFHR, 2012, pp. 367–372.
    18. 18)
      • 18. TELECOM & Management SudParis, BioSecure Multimodal Evaluation Campaign 2007 Mobile scenario – experimental results, Technical Report, (http://biometrics.it-sudparis.eu/BMEC2007/files/Results_mobile.pdf), 2007.
    19. 19)
      • 19. Yeung, D.Y., Chang, H., Xiong, Y., et al: ‘SVC2004: first international signature verification competition’. Proc. Int. Conf. on Biometric Authentication, ICBA, 2004 (LNCS3072), pp. 16–22.
    20. 20)
      • 20. Houmani, N., Garcia-Salicetti, S., Dorizzi, B.: ‘A novel personal entropy measure confronted with online signature verification systems’ performance’. Proc. IEEE Int. Conf. on Biometrics: Theory, Applications and Systems, BTAS, 2008, pp. 1–6.
    21. 21)
      • 21. Alonso-Fernandez, F., Fierrez-Aguilar, J., Ortega-Garcia, J.: ‘Sensor interoperability and fusion in signature verification: a case study using Tablet PC’. Proc. Int. Workshop on Biometric Recognition Systems, IWBRS, 2005, (LNCS3781), pp. 180–187.
    22. 22)
      • 22. Simsons, D., Spencer, R., Auer, S.: ‘The effects of constraining signatures’, J. Am. Soc. Questioned Doc. Examiners, 2011, 14, (1), pp. 39–50.
    23. 23)
      • 23. Richiardi, J., Ketabdar, H., Drygajlo, A.: ‘Local and global feature selection for on-line signature verification’. Proc. IAPR Eighth Int. Conf. on Document Analysis and Recognition, ICDAR, 2005, pp. 625–629.
    24. 24)
      • 24. Nelson, W., Kishon, E.: ‘Use of dynamic features for signature verification’. Proc. IEEE Int. Conf. on Systems, Man, and Cybernetics, 1991, vol. 1, pp. 201–205.
    25. 25)
    26. 26)
    27. 27)
    28. 28)
    29. 29)
    30. 30)
      • 30. Muramatsu, D., Matsumoto, T.: ‘Effectiveness of pen pressure, azimuth, and altitude features for online signature verification’. Proc. IAPR Int. Conf. on Biometrics, ICB, 2007 (LNCS4642), pp. 503–512.
    31. 31)
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