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On-line signature recognition based on VQ-DTW. (English) Zbl 1119.68172

Summary: This paper studies some pattern recognition algorithms for on-line signature recognition: Vector Quantization (VQ), Nearest Neighbor (NN), Dynamic Time Warping (DTW) and Hidden Markov Models (HMM). We have used a database of 330 users which includes 25 skilled forgeries performed by five different impostors. This database is larger than the typical ones found in the literature.Experimental results reveal that our first proposed combination of VQ and DTW (by means of score fusion) outperforms the other algorithms (DTW, HMM) and achieves a minimum Detection Cost Function (DCF) value equal to 1.37% for random forgeries and 5.42% for skilled forgeries. In addition, we present another combined DTW–VQ scheme which enables improvement of privacy for remote authentication systems, avoiding the submission of the whole original dynamical signature information (using codewords, instead of feature vectors). This system achieves similar performance than DTW.

MSC:

68T10 Pattern recognition, speech recognition
94A62 Authentication, digital signatures and secret sharing
94A34 Rate-distortion theory in information and communication theory
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[1] Nanavati, S.; Thieme, M.; Nanavati, R., Biometrics. Identity Verification in a Networked World (2002), Wiley: Wiley New York
[2] Jain, A.; Bolle, R.; Pankanti, S., Biometrics. Personal Identification in a Networked Society (1999), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht
[3] Zhang, D. D., Automated Biometrics. Technologies and Systems (2000), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht
[4] Faundez-Zanuy, M.; Monte-Moreno, E., State-of-the-art in speaker recognition, IEEE Aerosp. Electron. Syst. Mag., 20, 5, 7-12 (2005)
[5] \( \langle;\) http://www.biometricgroup.com \(\rangle;\); \( \langle;\) http://www.biometricgroup.com \(\rangle;\)
[6] \( \langle;\) http://www.cadix.com \(\rangle;\); \( \langle;\) http://www.cadix.com \(\rangle;\)
[7] \( \langle;\) http://www.wacom.com \(\rangle;\); \( \langle;\) http://www.wacom.com \(\rangle;\)
[8] Ortega-Garcia, J.; Gonzalez-Rodriguez, J.; Simon-Zorita, D.; Cruz-Llanas, S., From biometrics technology to applications regarding face, voice, signature and fingerprint recognition systems, (Biometrics Solutions for Authentication in an E-World (2002), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht), 289-337, (Chapter 12)
[9] Faundez-Zanuy, M., Privacy issues on biometric systems, IEEE Aerosp. Electron. Syst. Mag., 20, 2, 13-15 (2005)
[10] Faundez-Zanuy, M., Biometric recognition: why not massively adopted yet?, IEEE Aerosp. Electron. Syst. Mag., 20, 8, 25-28 (2005)
[11] Faundez-Zanuy, M., On the vulnerability of biometric security systems, IEEE Aerosp. Electron. Syst. Mag., 19, 6, 3-8 (2004)
[12] Faundez-Zanuy, M., Data fusion in biometrics, IEEE Aerosp. Electron. Syst. Mag., 20, 1, 34-38 (2005)
[13] Han, K.; Sethi, I. K., Handwritten signature retrieval and identification, Pattern Recognition Lett., 17, 83-90 (1996)
[14] Plamondon, R.; Lorette, G., Automatic signature verification and writer identification—the state of the art, Pattern Recognition, 1, 2, 107-131 (1989)
[15] Ortega-Garcia, J.; Fierrez, J.; Simon, D.; Gonzalez, J.; Faundez-Zanuy, M.; Espinosa, V.; Satue, A.; Hernaez, I.; Igarza, J.-J.; Vivaracho, C.; Escudero, D.; Moro, Q.-I., MCYT baseline corpus: a multimodal biometric database, IEE Proc.—Vision Image Signal Process., 150, 395-401 (2003)
[16] Jain, A. K.; Griess, F. D.; Connell, S. D., On-line signature verification, Pattern Recognition, 35, 2963-2972 (2002) · Zbl 1007.68938
[17] Lei, H.; Govindaraju, V., A comparative study on the consistency of features in on-line signature verification, Pattern Recognition Lett., 26, 2483-2489 (2005)
[18] Jain, A. K.; Duin, R. P.W.; Mao, J., Statistical pattern recognition: a review, IEEE Trans. Pattern Anal. Mach. Intell., 22, 1 (2000)
[19] Rabiner, L. R., A tutorial on hidden Markov models and selected applications in speech recognition, Proc. IEEE, 77, 2, 257-286 (1989)
[20] Rabiner, L.; Juang, B. H., An introduction to Hidden Markov models, IEEE ASSP Mag., 3, 1, 4-16 (1986)
[21] Xiao, X.; Leedham, G., Signature verification using a modified Bayesian network, Pattern Recognition, 35, 5, 983-995 (2002) · Zbl 0999.68573
[22] Nanni, L.; Lumini, A., Advanced methods for two-class problem formulation for on-line signature verification, Neurocomputing, 69, 7-9, 854-857 (2006)
[23] F. Soong, A. Rosenberg, L. Rabiner, B. Juang, A vector quantization approach to speaker recognition, IEEE Proceedings International Conference on Acoustics, Speech and Signal Processing ICASSP 1985, vol. 1, Tampa, 1985, pp. 387-390.; F. Soong, A. Rosenberg, L. Rabiner, B. Juang, A vector quantization approach to speaker recognition, IEEE Proceedings International Conference on Acoustics, Speech and Signal Processing ICASSP 1985, vol. 1, Tampa, 1985, pp. 387-390.
[24] A.L. Higgins, L.G. Bahler, J.E. Porter, Voice identification using nearest-neighbor distance measure, IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, 1993, pp. II-375-II-378.; A.L. Higgins, L.G. Bahler, J.E. Porter, Voice identification using nearest-neighbor distance measure, IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, 1993, pp. II-375-II-378.
[25] D. Yeung, H. Chang, Y. Xiong, S. George, R. Kashi, T. Matsumoto, G. Rigoll, SVC2004: First International Signature Verification Competition, Lecture Notes on Computer Science, vol. 3072, Springer, Berlin, 2004, pp. 16-22.; D. Yeung, H. Chang, Y. Xiong, S. George, R. Kashi, T. Matsumoto, G. Rigoll, SVC2004: First International Signature Verification Competition, Lecture Notes on Computer Science, vol. 3072, Springer, Berlin, 2004, pp. 16-22.
[26] Webb, A., Statistical Pattern Recognition (2002), Wiley: Wiley New York · Zbl 1102.68639
[27] Gersho, A.; Gray, R. M., Vector Quantization and Signal Compression (1991), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht
[28] Deller, J. R.; Proakis, J. G.; Hansen, J. H.L., Discrete-time Processing of Speech Signals (1987), Prentice-Hall: Prentice-Hall Englewood Cliffs
[29] Reynolds, D. A.; Rose, R. C., Robust text-independent speaker identification using Gaussian mixture speaker models, IEEE Trans. Speech and Audio Processing, 3, 1, 72-83 (1995)
[30] Guyon, I.; Makhoul, J.; Schwartz, R.; Vapnik, V., What size test set gives good error rate estimates?, IEEE Trans. Pattern Anal. Mach. Intell., 20, 1, 52-64 (1998)
[31] A. Martin, et al., The DET curve in assessment of detection performance, European Speech Processing Conference Eurospeech, vol. 4, 1997, pp. 1895-1898.; A. Martin, et al., The DET curve in assessment of detection performance, European Speech Processing Conference Eurospeech, vol. 4, 1997, pp. 1895-1898.
[32] C. Sanderson, Information fusion and person verification using speech & face information, IDIAP Research Report 02-33, September 2002, pp. 1-37.; C. Sanderson, Information fusion and person verification using speech & face information, IDIAP Research Report 02-33, September 2002, pp. 1-37.
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