Online Signature Analysis Based on Accelerometric and Gyroscopic Pens and Legendre Series

In this paper we compare two captured databases which contain local acceleration and angle information recorded during the signing process. Approximately a year passed between the capturing of the two databases and they contain several signatures from the same writers. We analyze the expedience of the proposed devices and examine the overlap of the databases using Legendre approximation for feature computation and Support Vector Machine for classification. In addition we plan to make the concerned databases publicly available for research purposes.

[1]  Hongyan Zhao,et al.  Offset Approximation Along the Offset Direction for Planar Curve , 2011, 2011 Fourth International Symposium on Computational Intelligence and Design.

[2]  Hong Chang,et al.  SVC2004: First International Signature Verification Competition , 2004, ICBA.

[3]  János Csirik,et al.  The Effect of Training Data Selection and Sampling Time Intervals on Signature Verification , 2011, AFHA.

[4]  János Csirik,et al.  Online Signature Verification Method Based on the Acceleration Signals of Handwriting Samples , 2011, CIARP.

[5]  S. Venkatesan,et al.  Dynamic Signature Verification Using Embedded Sensors , 2011, 2011 International Conference on Body Sensor Networks.

[6]  Muzaffar Bashir,et al.  Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device , 2008 .

[7]  G. Gladwell,et al.  A Legendre Approximation Method for the Circular Microstrip Disk Problem , 1977 .

[8]  Juan Carlos Gómez,et al.  Online Signature Verification Based on Legendre Series Representation. Consistency Analysis of Different Feature Combinations , 2012, CIARP.

[9]  Raymond N. J. Veldhuis,et al.  Spectral minutiae: A fixed-length representation of a minutiae set , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[10]  Raymond N. J. Veldhuis,et al.  Practical Biometric Authentication with Template Protection , 2005, AVBPA.

[11]  C. N. Liu,et al.  Automatic signature verification based on accelerometry , 1977 .

[12]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[13]  Réjean Plamondon,et al.  Acceleration measurement with an instrumented pen for signature verification and handwriting analysis , 1989 .

[14]  Daniel Howard,et al.  MALDI-TOF Baseline Drift Removal Using Stochastic Bernstein Approximation , 2006, EURASIP J. Adv. Signal Process..

[15]  Berrin A. Yanikoglu,et al.  Identity authentication using improved online signature verification method , 2005, Pattern Recognit. Lett..

[16]  Katalin Kopasz,et al.  Edaq530: a transparent, open-end and open-source measurement solution in natural science education , 2010 .

[17]  Marcus Liwicki,et al.  A Signature Verification Framework for Digital Pen Applications , 2012, 2012 10th IAPR International Workshop on Document Analysis Systems.

[18]  Marcus Liwicki,et al.  Online Signature Verification Based on Legendre Series Representation: Robustness Assessment of Different Feature Combinations , 2012, 2012 International Conference on Frontiers in Handwriting Recognition.

[19]  V. Matousek,et al.  Signature verification using ART-2 neural network , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..