Hidden Signature for DTW Signature Verification in Authorizing Payment Transactions
DOI:
https://doi.org/10.26636/jtit.2010.4.1097Keywords:
dynamic time warping, hidden signature, payment transactions, signature verificationAbstract
Traditional use of dynamic time warping for signature verification consists of forming some dissimilarity measure between the signature in question and a set of "template signatures". In this paper, we propose to replace this set with the hidden signature and use it to calculate the normalized errors of signature under verification. The approach was tested on the MCYT database, using both genuine signatures and skilled forgeries. Moreover, we present the real-world application of the proposed algorithm, namely the complete biometric system for authorizing payment transactions. The authorization is performed directly at a point of sale by the automatic signature verification system based on the hidden signature.
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References
[1] N. Herbst and C. Liu, „Automatic signature verification based on accelerometry”, IBM J. Res. Develop., vol. 21, no. 3, pp. 245-253, 1977.
View in Google Scholar
[2] D. Sakamoto, H. Morita, T. Ohishi, Y. Komiya, and T. Matsumoto, „On-line signature verifier incorporating pen position, pen pressure and pen inclination trajectories”, in Proc. 3rd Int. Conf. AVBPA 2001, Halmstad, Sweden, 2001, pp. 318-323.
View in Google Scholar
[3] A. Pacut and J. Putz-Leszczyńska, „Dynamic time warping in sub-spaces for on-line signature verification”, in Proc. 12th Conf. Int. Graphonom. Soc. IGS 2005, Salerno, Italy, 2005, pp. 108-112.
View in Google Scholar
[4] A. Kholmatov and B. Yanikoglu, „Identity authentication using improved online signature verification method”, Pattern Recogn. Lett., vol. 26, no. 15, pp. 2400-2408, 2005.
View in Google Scholar
[5] O. Miguel-Hurtado, L. Mengibar-Pozo, M. Lorenz, and J. Liu-Jimenez, „On-line signature verification by dynamic time warping and Gaussian mixture models”, in 41st Ann. IEEE Int. Carnahan Conf. Secur. Technol., Ottawa, Canada, 2007, pp. 23-29.
View in Google Scholar
[6] B. Fang et al., „Off-line signature verification by the tracking of feature and stroke positions”, Pattern Recogn., vol. 36, pp. 91-101, 2003.
View in Google Scholar
[7] J. Putz-Leszczyńska and A. Pacut, „‘Hidden signature’ - a new solution for on-line verification”, in 42nd Ann. IEEE Int. Carnahan Conf. Secur. Technol., Prague, Czech Republic, pp. 68-73, 2008.
View in Google Scholar
[8] J. Putz-Leszczyńska, „On-line signature verification using dynamic time warping with positional coordinates”, in Proc. SPIE, vol. 6347, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments, R. S. Romaniuk, Ed., 2006 (doi: 10.1117/12.714578).
View in Google Scholar
[9] Z.-H. Quan, D.-S. Huang, X.-L. Xia, M. R. Lyu, and T.-M. Lok, „Spectrum analysis based on windows with variable widths for online signature verification”, in Proc. 18th Int. Conf. Pattern Recogn. ICPR 2006, Hong Kong, China, 2006, vol. 2, pp. 1122-1125.
View in Google Scholar
[10] B. Ly Van, S. Garcia-Salicetti, and B. Dorizzi, „On using the Viterbi path along with HMM likelihood information for online signature verification”, IEEE Trans. Sys. Man. Cybernetics, Part B: Cybernetics, vol. 37, no. 5, 2007.
View in Google Scholar
[11] D. Guru and H. Prakash, „Symbolic representation of on-line signatures”, in Proc. Int. Conf. Comput. Intellig. Multimedia Appl. 2007, Sivakasi, India, 2007, pp. 313-317.
View in Google Scholar
[12] J. Galbally, J. Fierrez, M. Freire, and J. Ortega-Garcia, „Feature selection based on genetic algorithms for on-line signature verification”, in Proc. IEEE Worksh. Autom. Identif. Adv. Technol. 2007, Alghero, Italy, 2007, pp. 198-203.
View in Google Scholar
[13] M. Faundez-Zanuy, „On-line signature recognition based on VQ-DTW”, Pattern Recogn., vol. 40, no. 3, pp. 981-992, 2007.
View in Google Scholar
[14] L. Nanni and A. Lumini, „A novel local on-line signature verification system”, Pattern Recogn. Lett., vol. 29, no. 5, pp. 559-568, 2008.
View in Google Scholar
[15] B. Yanikoglu and A. Kholmatov, „Online signature verification using Fourier descriptors”, EURASIP J. Adv. Sig. Proces., 2009.
View in Google Scholar
[16] J. Ortega-Garcia et al., „MCYT baseline corpus: a bimodal biometric database”, IEE Proc.-Vis. Image Sig. Process., vol. 150, no. 6, pp. 395-401, 2003.
View in Google Scholar
[17] H. Sakoe and S. Chiba, „Dynamic programming algorithm optimization for spoken word recognition”, IEEE Trans. Acoust., Speech Sig. Proces., vol. 26, no. 1, pp. 43-49, 1978.
View in Google Scholar
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