Abstract
In this paper, a pre-classification stage based on global features is incorporated to an online signature verification system for the purposes of improving its performance. The pre-classifier makes use of the discriminative power of some global features to discard (by declaring them as forgeries) those signatures for which the associated global feature is far away from its respective mean. For the remaining signatures, features based on a wavelet approximation of the time functions associated with the signing process, are extracted, and a Random Forest based classification is performed. The experimental results show that the proposed pre-classification approach, when based on the apppropriate global feature, is capable of getting error rate improvements with respect to the case where no pre-classification is performed. The approach also has the advantages of simplifying and speeding up the verification process.
Chapter PDF
Similar content being viewed by others
References
Impedovo, D., Pirlo, G.: Automatic signature verification: The state of the art. IEEE Trans. on Syst., Man, and Cybern. - Part C: Appl. and Reviews 38(5), 609–635 (2008)
Maramatsu, D., Matsumoto, T.: Effectiveness of pen pressure, azimuth, and altitude features for online signature verification. In: Proc. of Int. Conf. on Biomet., pp. 503–512 (2007)
Yanikoglu, B., Kholmatov, A.: Online signature verification using fourier descriptors. EURASIP J. on Advances in Signal Process., 230–275 (2009)
Richiardi, J., Ketabdar, H., Drygajlo, A.: Local and global feature selection for on-line signature verification. In: Proc. of 8th Int. Conf. on Doc. Anal. and Recognit., Seoul, Korea (2005)
Fierrez-Aguilar, J., Nanni, L., Lopez-Peñalba, J., Ortega-Garcia, J., Maltoni, D.: An on-line signature verification system based on fusion of local and global information. In: Proc. IAPR Int. Conf. on Audio- and Video-Based Biomet. Person Authentic., New York, NY, USA, pp. 523–532 (2005)
Plamondon, R.: The design of an on-line signature verification system: from theory to practice. Int. J. on Pattern Recognit. and Artif. Intell. 8(3), 795–811 (1994)
Lee, L.L., Berger, T., Aviczer, E.: Reliable on-line human signature verification systems. IEEE Trans. on Pattern Anal. and Machine Intell. 18(6), 643–647 (1996)
Fierrez-Aguilar, J., Ortega-Garcia, J., Ramos-Castro, D., Gonzalez-Rodriguez, J.: HMM-based on-line signature verification: Feature extraction and signature modelling. Pattern Recognit. Lett. 28, 2325–2334 (2007)
Parodi, M., Gómez, J.C., Liwicki, M.: Online signature verification based on legendre series representation. Robustness assessment of different feature combinations. In: Proc. of 13th Int. Conf. on Frontiers in Handwriting Recognit, Bari, Italy, pp. 377–382 (September 2012)
Daubechies, I.: Ten Lectures on Wavelets. SIAM, Pennsylvania (1992)
Liwicki, M., Malik, M.I., den Heuvel, C.E., Chen, X., Berger, C., Stoel, R., Blumenstein, M., Found, B.: Signature verification competition for online and offline skilled forgeries (SigComp2011). In: Proceedings of 11th Int. Conf. on Doc. Anal. and Recognit., Beijing, China (September 2011)
Breiman, L.: Random forests. Technical report, Stat. Dep., Univ. of California, Berkeley (2001)
Gonzalez-Rodriguez, J., Fierrez-Aguilar, J., Ramos-Castro, D., Ortega-Garcia, J.: Bayesian analysis of fingerprint, face and signature evidences with automatic biometric systems. Forensic Sci. Int. 155, 126–140 (2005)
Brümmer, N., du Preez, J.: Application-independent evaluation of speaker detection. Comput. Speech & Language 20, 230–275 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Parodi, M., Gómez, J.C. (2013). Online Signature Verification: Improving Performance through Pre-classification Based on Global Features. In: Petrosino, A., Maddalena, L., Pala, P. (eds) New Trends in Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41190-8_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-41190-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41189-2
Online ISBN: 978-3-642-41190-8
eBook Packages: Computer ScienceComputer Science (R0)