Embedded Platform For Online Signature Verification

Sangeet Kumar K, V.V.S.R.K.K.Pavan BH

Abstract


in my project the proposed system is used for verifying the signature of particular person with help of embedded plat form on mobile devices. This paper studies online signature verification on PC interface-based mobile devices. A simple and effective method for signature verification is developed. An online signature is represented with a discriminative feature vector derived from attributes of several histograms that can be computed in linear time. The resulting signature template is compact and requires constant space. The algorithm used in this project is SVM (support vector machine). The signatures are acquired using a digitizing tablet which captures both dynamic and spatial information of the writing. After preprocessing the signature, several features are extracted. The authenticity of a writer is determined by comparing an input signature to a stored reference set (template) consisting of three signatures. The similarity between an input signature and the reference set is computed using string matching and the similarity value is compared to a threshold. Several approaches for obtaining the optimal threshold value from the reference set are investigated. The results demonstrate the problem of within-user variation of signatures across multiple signatures and the effectiveness of cross session training strategies to alleviate these problems.


References


N. SAE-BAE, K. AHMED, K. ISBISTER, AND N. MEMON, “BIOMETRIC-RICH GESTURES: A NOVEL APPROACH TO AUTHENTICATION ON MULTI-TOUCH DEVICES,” IN PROC. CHI, 2012, PP. 977–986.

N. Sae-Bae, N. Memon, K. Isbister, And K. Ahmed, “Multitouch Gesturebased Authentication,” Ieee Trans. Inf. Forensics Security, Vol. 9, No. 4,

Pp. 568–582, Apr. 2014.

J. Fierrez, J. Ortega-Garcia, D. Ramos, And J. Gonzalez-Rodriguez, “Hmm-Based On-Line Signature Verification: Feature Extraction And

Signature Modeling,” Pattern Recognit. Lett., Vol. 28, Pp. 2325–2334, Dec. 2007.

E. Maiorana, P. Campisi, J. Fierrez, J. Ortega-Garcia, And A. Neri, “Cancelable Templates For Sequence-Based Biometrics With Application To

On-Line Signature Recognition,” Ieee Trans. Syst., Man, Cybern. A, Syst., Humans, Vol. 40, No. 3, Pp. 525–538, May 2010.

E. Maiorana, P. Campisi, And A. Neri, “Template Protection For Dynamic Time Warping Based Biometric Signature Authentication,” In Proc. 16th Int. Conf. Digital Signal Process., Jul. 2009, Pp. 1–6.

L. G. Plamondon And R. Plamondon, “Automatic Signature Verification And Writer Identification—The State Of The Art,” Pattern Recognit., Vol. 22, No. 2, Pp. 107–131, 1989.

H. Feng And C. C. Wah, “Online Signature Verification Using A New Extreme Points Warping Technique,” Pattern Recognit. Lett., Vol. 24,

No. 16, Pp. 2943–2951, 2003.

A. Kholmatov And B. Yanikoglu, “Susig: An On-Line Signature Database, Associated Protocols And Benchmark Results,” Pattern Anal. Appl.,

Vol. 12, No. 3, Pp. 227–236, 2008.

J. Ortega-Garcia Et Al., “Mcyt Baseline Corpus: A Bimodal Biometric Database,” Iee Proc. Vis. Image Signal Process., Vol. 150, No. 6,

Pp. 395–401, Dec. 2003.

L. Nanni, “An Advanced Multi-Matcher Method For On-Line Signature Verification Featuring Global Features And Tokenised Random Numbers,” Neurocomputing, Vol. 69, Nos. 16–18, Pp. 2402–2406, 2006.

D. Guru And H. Prakash, “Online Signature Verification And Recognition: An Approach Based On Symbolic Representation,” Ieee Trans. Pattern

Anal. Mach. Intell., Vol. 31, No. 6, Pp. 1059–1073, Jun. 2009.

J. Galbally, M. Martinez-Diaz, And J. Fierrez, “Aging In Biometrics: An Experimental Analysis On On-Line Signature,” Plos One, Vol. 8, No. 7, P. E69897, 2013.

M. Faundez-Zanuy, “On-Line Signature Recognition Based On Vq-Dtw,” Pattern Recognit., Vol. 40, No. 3, Pp. 981–992, 2007.

P. Song, W. B. Goh, C.-W. Fu, Q. Meng, And P.-A. Heng, “Wysiwyf: Exploring And Annotating Volume Data With A Tangible Handheld Device,” In Proc. Sigchi Conf. Human Factors Comput. Syst.,2011, Pp. 1333–1342.

A. Fallah, M. Jamaati, And A. Soleamani, “A New Online Signature Verification System Based On Combining Mellin Transform, Mfcc And Neural Network,” Digital Signal Process., Vol. 21, No. 2, Pp. 404–416, 2011.

L. Findlater, J. O. Wobbrock, And D. Wigdor, “Typing On Flat Glass: Examining Ten-Finger Expert Typing Patterns On Touch Surfaces,” In Proc. Annu. Conf. Human Factors Comput. Syst., New York, Ny, Usa, 2011, Pp. 2453–2462.

P. Tome-Gonzalez, F. Alonso-Fernandez, And J. Ortega-Garcia, “On The Effects Of Time Variability In Iris Recognition,” In Proc. 2nd Ieee Int.

Conf. Btas, Oct. 2008, Pp. 1–6.

G. Rigoll, A. Kosmala, A Systematic Comparison Between On-Line And Off-Line Methods For Signature Verification With Hidden Markov Models, In: Proceedings Of The International Conference On Pattern Recognition, Vol. 2, 1998, Pp. 1755 –1757.

R. Martens, L. Claesen, Dynamic Programming Optimization For On-Line Signature Verification, In: Proceedings Of The International Conference On Document Analysis And Recognition, 1997, Pp. 653– 656.

Y.K.T. Ohishi, T. Matsumoto, On-Line Signature Verification Using Pen-Position, Pen-Pressure And Pen-Inclination Trajectories, In: Proceedings Of The International Conference On Pattern Recognition, 2000, Pp. 547–550.


Full Text: PDF[FULL TEXT]

Refbacks

  • There are currently no refbacks.


Copyright © 2013, All rights reserved.| ijseat.com

Creative Commons License
International Journal of Science Engineering and Advance Technology is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJSEat , Permissions beyond the scope of this license may be available at http://creativecommons.org/licenses/by/3.0/deed.en_GB.