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Hidden Signature for DTW Signature Verification in Authorizing Payment Transactions

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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.
Rocznik
Tom
Strony
59--67
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
autor
Bibliografia
  • [1] N. Herbst and C. Liu, “Automatic signature verification based on accelerometry”, in IBM J. Res. Develop., pp. 245–253, 1977.
  • [2] D. Sakamoto, H. Morita, T. Ohishi, Y. Komiya, and T. Matsumoto, “On-line signature verifier incorporating pen position, pen pressure and pen inicliation trajectories”, in Proc. 3rd Int. Conf. AVBPA 2001, Halmstad, Sweden, 2001, pp. 318–323.
  • [3] A. Pacut and J. Putz-Leszczyńska, “Dynamic time warping in subspaces for on-line signature verification”, in Proc. 12th Conf. Int. Graphonom. Soc. IGS 2005, Salerno, Italy, 2005, pp. 108–112.
  • [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.
  • [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.
  • [6] B. Fang, C. Leung, Y. Tang, K. Tseb, P. Kwokd, and Y. Wonge, “Off-line signature verifcation by the tracking of feature and stroke positions”, Pattern Recogn., vol. 36, pp. 91–101, 2003.
  • [7] A. Putz-Leszczyńska, J.and Pacut, “‘Hidden signature’ – a new solution for on-line verification ”, in 42nd Ann. IEEE Int. Carnahan Conf. Secur. Technol., Prague, Czech Rebulic, pp. 68–73, 2008.
  • [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).
  • [9] X.-L. X. M. R. L. Z.-H. Quan, D.-S. Huang and T.-M. Lok, “Spectrum analysis based on windows with variable widths for online sig- nature verification”, in Proc. 18th Int. Confe. Pattern Recogn. ICPR 2006), Hong Kong, China, 2006, vol. 2, pp. 1122–1125.
  • [10] B. L. 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.
  • [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.
  • [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.
  • [13] M. Faundez-Zanuy, “On-line signature recognition based on VQ- DTW”, Pattern Recogn., vol. 40, no. 3, pp. 981–992, 2007.
  • [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.
  • [15] B. Yanikoglu and A. Kholmatov, “Online signature verification using fourier descriptors”, EURASIP J. Adv. Sig. Proces., 2009.
  • [16] J. Ortega-Garcia, J. Fierrez-Aguilar, D. Simon, J. Gonzalez, M. Faundez-Zanuy, V. Espinosa, A. Satue, I. Hernaez, J.-J. Igarza, C. Vivaracho, D. Escudero, and Q.-I. Moro, “MCYT baseline corpus: a bimodal biometric database”, IEE Proc.-Vis. Image Sig. Process., vol. 150, no. 6, pp. 3412–3426, 2003.
  • [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.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT8-0020-0018
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