Abstract
Person identification or verification is becoming an important issue in our life with the growth of information technology. Handwriting features of individuals during signing are used as behavioral biometrics. This paper presents a new method for recognizing person using online signatures based on reference level assigned Dynamic Time Warping (DTW) algorithm. The acquisition of online data is carried out by a digital pen equipped with pressures and inclination sensors. The time series obtained from pen during handwriting provide valuable insight to the unique characteristics of the writers. The obtained standard deviation values of time series are found person specific and are used as so called reference levels. In the proposed method reference levels are added to time series of query and sample dataset before dynamic time warping distance calculations. Experimental results show that the performance of accuracy in person authentication is improved and computational time is reduced.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Impedovo, D., Modugno, R., Pirlo, G., Stasolla, E.: Handwritten Signature Verification by Multiple Reference Set. In: Int. Conf. on Frontiers in Handwriting Recognition ICFHR (2008)
Keogh, E.J., Pazzani, M.J.: Scaling up dynamic Time Warping for Data mining Applications. In: Proc. 6th Int. Conf. on Knowlegde Discovery and Data Mining. KDD (2000)
Bashir, M., Kempf, J.: Reduced Dynamic Time Warping for Handwriting Recognition Based on Multi-dimensional Time Series of a Novel Pen Device. In: IJIST, WASET, Paris, vol. 3.4 (2008)
Zhang, J., Kamata, S.: Online Signature Verification Using Segment-to-Segment Matching. In: Int. Conf. on Frontiers in Handwriting Recognition ICFHR (2008)
Hao, F., Wah, C.C.: Online signature verification using a new extreme points warping technique. In: Pattern recognition, vol. 24. Elsevier Science, NY (2003)
Bashir, M., Kempf, J.: Person Authentication with RDTW using Handwritten PIN and signature with a Novel Biometric Smart Pen Device. In: SSCI Computational Intelligence in Biometrics. IEEE, Nashville (2009)
Keogh, E., Ratanamahatana, C.A.: Exact indexing of dynamic time warping. In: Knowledge and Information Systems, pp. 358–386. Springer, London (2004)
Henniger, O., Muller, S.: Effects of Time Normalization on the Accuracy of Dynamic Time Warping. In: BTAS, pp. 27–29. IEEE, Los Alamitos (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bashir, M., Kempf, J. (2009). Bio-Inspired Reference Level Assigned DTW for Person Identification Using Handwritten Signatures. In: Fierrez, J., Ortega-Garcia, J., Esposito, A., Drygajlo, A., Faundez-Zanuy, M. (eds) Biometric ID Management and Multimodal Communication. BioID 2009. Lecture Notes in Computer Science, vol 5707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04391-8_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-04391-8_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04390-1
Online ISBN: 978-3-642-04391-8
eBook Packages: Computer ScienceComputer Science (R0)