Signature Security System for E-Commerce

The study of human signatures has a long history, but automatic signature verification is still a new and active topic in the research and application fields of biometrics. This chapter starts with a detailed survey of recent research progress and commercial products in automatic dynamic verification. Instead of applying new and popular approaches, such as those of Artificial Neural Networks, Fuzzy Logic, or the Hidden Markov Model, this chapter proposes a low cost on-line dynamic signature verification method based on the combination of time-dependent global coordinate features and local curvature features. Global features include pen down time, pen down move, the average, maximum and standard deviation of both the velocity and acceleration, while local features make use of the time dependent relationship between adjacent curative turning points. The astonishing growth of the Internet and intranet raises the new challenge of e-commerce security. With the attempts to look for a low cost biometrics method as an enhancement of personal identification in the network, a typical system for dynamic signature verification in the Internet and intranet is introduced. This system involves such processes as dynamic signature data acquisition through the network, using global and local feature extraction, feature match, feature enrollment, and combined feature comparison for verification and distance measures for recognition. Finally, this chapter proposes some applications of on-line signature verification.

[1]  Réjean Plamondon,et al.  Automatic signature verification and writer identification - the state of the art , 1989, Pattern Recognit..

[2]  Luan Ling Lee.  Neural approaches for human signature verification , 1996, Proceedings of Third International Conference on Signal Processing (ICSP'96).

[3]  Ronny Martens,et al.  On-line signature verification: discrimination emphasised , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[4]  L. Rabiner,et al.  An introduction to hidden Markov models , 1986, IEEE ASSP Magazine.

[5]  Ronny Martens,et al.  On-line signature verification by dynamic time-warping , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[6]  V. S. Nalwa.  Automatic on-line signature verification , 1997 .

[7]  Réjean Plamondon.  Progress in Automatic Signature Verification , 1994 .

[8]  Michael C. Fairhurst,et al.  Parallelism in dynamic time warping for automatic signature verification , 1995, Proceedings of 3rd International Conference on Document Analysis and Recognition.

[9]  William Turin,et al.  Statistical Methods for On-Line Signature Verification , 1994, Int. J. Pattern Recognit. Artif. Intell..

[10]  L. Yang,et al.  Application of hidden Markov models for signature verification , 1995, Pattern Recognit..

[11]  Emile H. L. Aarts,et al.  On-line signature verification with hidden Markov models , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[12]  Brigitte Wirtz.  Stroke-based time warping for signature verification , 1995, Proceedings of 3rd International Conference on Document Analysis and Recognition.

[13]  M. J. Paulik,et al.  Multi-layer neural network classification of on-line signatures , 1996, Proceedings of the 39th Midwest Symposium on Circuits and Systems.

[14]  Sargur N. Srihari,et al.  On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  M. J. Paulik,et al.  A time varying vector autoregressive model for signature verification , 1994, Proceedings of 1994 37th Midwest Symposium on Circuits and Systems.

[16]  H. Sakai,et al.  On stochastic system representation of handwriting process and its application to signature verification , 1996, Proceedings of Third International Conference on Signal Processing (ICSP'96).

[17]  Rynson W. H. Lau,et al.  A signature based password authentication method , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.