Authentication Based on Modeling of the Signature Velocity

Rashidi, Saeed; Fallah, Ali; Towhidkhah, Farzad

doi:10.22041/ijbme.2010.13299

Document Type : Full Research Paper

Authors

¹ Instructor, Bioelectric Group, School of Biomedical Engineering, Science and Research Branch, Islamic Azad University

² Assistant Professor, Bioelectric Group, School of Biomedical Engineering, Amir Kabir University of Technology

³ Associate Professor, Bioelectric Group, School of Biomedical Engineering, Amir Kabir University of Technology

10.22041/ijbme.2010.13299

Abstract

Nowadays, fast and accurate algorithms for signature verification are very attractive. In the area of dynamic signature verification, the features are classified into two groups: parametric and functional features. In parametric algorithms, although the speed of features extraction and classification process is faster than function based approaches but they are less accurate. The goal of this paper is modeling of the velocity signal that its pattern and properties are stable for a person. With using pole-zero models based on discrete cosine transform, a precise method is proposed for modeling and then features are extracted from strokes. These features are the deference of pole angles of strokes. Applying linear, parzen window and support vector machine classifiers, the proposed algorithm was tested on data set from Persian, Chinese, English and Turkish people and with common threshold, resulted equal error rates of 1.25% and 1.78% in the random and skilled forgeries, respectively.

Keywords

References

[1] Plamondon R., Lorette G., Automatic signature verification and writer identification: The state of the art; Pattern Recognition; 1989; 22: 107-131.

[2] Plamondon R., Srihari S. N., On-line and off-line handwriting recognition: A comprehensive survey; IEEE Trans. Pattern Anal. Machine Intelligence, 2000; 22 (1): 63-84.

[3] Plamondon R., Parizeau M., Signature verification from position, velocity and acceleration signal: A comparative study; Proc. of 9th Int. Conference on Pattern Recognition Italy, 1988; 1: 260-265.

[4] Fierrez-Aguilar J., Nanni L., Lopez-Penalba J., Ortega-Garcia J., Maltoni D., An on-line signature verification system based on fusion of local and global information; Audio and Video Based Biometric Person Authentication; Lecture Note in Computer Science; Springer; Berlin, 2005: 523-532.

[5] Nanni L., Experimental comparison of one-class classifier for online signature verification; Neurocomputing; 2006; 69: 869-873.

[6] Faundez-Zanuy M., On-line signature recognition based on vq-dtw; Pattern Recognition; 2007, 40 (3): 981-992.

[7] Vivaracho-Pascual C., Faundez-Zanuy M., Pascual J. M., An efficient low cost approach for on-line signature verification based on length normalization and fractional distances; Pattern Recognition, 2009; 42: 183-193.

[8] Nanni L., Lumini A., Advanced methods for two-class problem formulation for on-line signature verification; Neurocomputing; 2006, 69: 854-877.

[9] Nanni L., Lumini A., A novel local on-line signature verification system; Pattern Recognition Letters, 2008; 29 (5): 559-568.

[10] Yanikoglu B., Kholmatov A., On-line signature verification using fourier descriptors; J. on Advances in Signal Processing; In Press.

[11] Yi J., Lee C., Kim J., Online signature verification using temporal shift estimated by the phase of gabor filter; IEEE Transactions on Signal Processing, 2005; 53: 776-783.

[12] Jain A.K., Griess F.D., Connell S.D., Online signature verification; Pattern Recognition; 2002; 35 (12): 2963-2972.

[13] Kholmatov A., Yanikogla B., Identity authentication using improved online signature verification method; Pattern Recognition Letters, 2005; 26 (15): 2400-2408.

[14] Ly Van B., Garcia-Salicetti S., Dorizzi B., On using the viterbi path along with hmm likelihood information for on-line signature verification; IEEE Trans. on Systems, Man and Cybernetics Part B, Special Issue on Recent Advances in Biometric Systems, 2007; 37 (5): 1237-1247.

[15] Fierrez J., Garcia J. O., Ramos D., Rodriguez J. G., HMM-based on-line signature verification: Features extraction and signature modeling; Pattern Recognition Letters, 2007; 28 (16): 2325-2334.

[16] Mohankrishnan N., Paulik M.J., Khalil M., Online signature verification using a nonstationary autoregressive model representation; Proc. Of the IEEE Int. Symposium on Circuits and Systems; Chicago, 1993: 2303-2306.

[17] Lee W.S., Mohankrishnan N., Paulik M.J., Improvement segmentation through dynamic time warping for signature verification using a neural network classifier; Int. Conference on Image Processing, Michigan, 1998: 929-933.

[18] Thumwarin P., Suthithummathat N., Matsuura T., Online signature verification based on time-frequency characteristics of barycenter trajectory; 4th Int. Conference on Electrical, Computer, Telecommunications and Information Technology, 2007: 521-524.

[19] رشیدی سعید، فلاح علی، توحیدخواه فرزاد؛ تصدیق امضاء از دیدگاه فرضیه کنترل حرکات ماهرانه؛ مجله مهندسی پزشکی زیستی؛ 1386؛ 1 (4): 269-280.

[20] SVC. The First International Signature Verification Competition; http://www.cs.ust.hk/svc2004.

[21] Kholmatov A., Yanikoglu B., Susig: an on-line signature database, associated protocols and benchmark results; Pattern Analysis & Applications, 2008: 20-26.

[22] رشیدی سعید، فلاح علی، توحیدخواه فرزاد؛ احراز اصالت هویت فرد با استفاده از مدلسازی منحنی سرعت الگوی امضاء؛ ششمین کنفرانس بین‌المللی انجمن رمز؛ دانشگاه اصفهان؛ 1388: 269- 276.

[23] رشیدی سعید، فلاح علی، توحیدخواه فرزاد؛ مقایسه ویژگی‌های سیگنالی با استفاده از الگوریتم اصلاح شده DTW در مسئله تصدیق امضای پویا؛ مجله مهندسی پزشکی زیستی، 1389؛ 4 (2): 135-148.

[24] رشیدی سعید، فلاح علی، توحیدخواه فرزاد؛ سیستم تصدیق امضای پویای دو مرحله‌ای مبتنی بر ویژگی‌های پارامتری و سیگنالی؛ شانزدهمین کنفرانس مهندسی پزشکی ایران؛ دانشگاه تهران؛ 1388.

[25] Lacquaniti F., Terzuolo C.A., Viviani P., The law relating kinematics and figural aspects of drawing movements; Acta Psychologica, 1983; 54: 115-130.

[26] Plamondon R., Maarse F.J., An evaluation of motor models of handwriting; IEEE Trans. on System, Man and Cybernetics, 1989; 19 (5): 1060-1072.

[27] Murthy I.S.N., Durga Prasad G.S.S., Analysis of ECG from pole-zero model; IEEE Trans. on Biomedical Eng., 1992; 39 (7): 741-751.

[28] Madhukar B., Murthy I.S.N., ECG data compression by modeling; Computational Biomedical Res., 1993; 26: 310-317.

[29] Yeung D. Y., Chang H., Xiong Y., George S., Kashi R., Matsumoto T., Rigoll G., SVC2004: First international signature verification competition; In Proc. of Int. Conf. on Biometric Authentication; Springer LNCS-3072, 2004: 16-22.

[30] Fierrez-Aguilar J., Adapted Fusion Schemes for Multimodal Biometric Authentication; PHD Thesis; Univ. Madrid, 2006.

[31] Doroz R., Porwik P., Para T., Wrobel K., Dynamic Signature Recognition Based on Velocity Change of Some Features; Int. J. Biometrics, 2008; 1 (1): 47-62.

[32] Ragot N., Fortune J., Vincent N., Cardot H., Study of temporal variability in on-line signature verification; The 11th Int. Conference on Frontiers in Handwriting Recognition; Montreal Canada, 2008: 556-561.

[33] Yanikoglu B., Kholmatov A., On-line signature verification using Fourier descriptors; J. on Advances in Signal Processing, 2009.

Iranian Journal of Biomedical Engineering

Authentication Based on Modeling of the Signature Velocity

References

References

Volume 4, Issue 3 - Serial Number 3
June 2010
Pages 219-230

Authentication Based on Modeling of the Signature Velocity

References

References

Volume 4, Issue 3 - Serial Number 3June 2010Pages 219-230

Volume 4, Issue 3 - Serial Number 3
June 2010
Pages 219-230