Volume- 3
Issue- 2
Year- 2015
Article Tools: Print the Abstract | Indexing metadata | How to cite item | Email this article | Post a Comment
Ch.Ayyappa , S. Manikandaswamy
This paper describes the implementation biometric of an embedded system for online signature verification using ARM processor. Online signature verification is one of the biometric features which can be used as a common method for identity verification. The online signature verification is the aim of difference between the original signature and forgery signature. The online signature verification is primarily focused on skilled forgery detection. The signatures are acquired using a digitizing tablet which captures both dynamic and spatial information of the writing. After pre-processing 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 best result yields a false reject rate of 2.8% and a false accept rate of 1.6%. The On-line Signature Recognition and Verification is implemented using MATLAB. This work has been tested and found suitable for its purpose.
[1] O. Miguel-Hurt ado, “Online Signature Verification Algorithms and Development of Signature International Standards” Ph.D. dissertation, Universidad Carlos III de Madrid, Madrid, Spain, 2011.
[2] O. Miguel-Hurt ado, L. Mengibar-Pozo, and A. Pacut, “A new algorithm for signature verification system based on DTW and GMM” in Proc. 42nd. Annu. IEEE Int. Carnahan Conf. Security Technol., Oct. 2008.
[3] S.D. Connell, Online handwriting recognition using multiple pattern class models, Ph.D. Thesis, MSU-CSE-00-27, Department of Computer Science, Michigan State University, and May 2000.
[4] D. Impedovo and G. Pirlo, “Automatic signature verification: The state of the art,” IEEE Trans. Syst., Man, Cyber. —Part C: Appl. Rev., vol. 38, no. 5, pp. 609–635, Sep. 2008.
[5] Ma, M. M., W. S. Wijesoma, and E. Sung. 2000. An Automatic On-line Signature Verification System based on Three Models. Proceedings of Conference on Electrical and Computer Engineering. Halifax (NS). 890-894.
[6] R. Plamondon and S.N. Srihari, "Online and Offline Handwriting Recognition: A Comprehensive Survey", IEEE Tran. On Pattern Analysis and Machine Intelligence, vol.22 no.1, pp.63-84, Jan.2000.
[7] Shafiei, M. M. and H. R. Rabiee. 2003. A New On-line Signature Verification Algorithm Using Variable Length Segmentation and Hidden Markov Models. Proceedings of the 7th International Conference on Document Analysis and Recognition. 443-446.
[8] http://www.signotec.com.
[9] Jain, A., Griess, F., and Connel1, S. “Online Signature Recognition”, Pattern Recognition, vol.35,2002, pp 29632972
[10] http://www.securedsigning.com
Department of Electronics and Communication Engineering,(Embedded System Technology), SRM University, Chennai, India, Mobile No +918122909138
No. of Downloads: 7 | No. of Views: 9716
Dr. Ch. Manohar Kumar, S. Yaswanth, B. Venkata Sai Teja, K. Akhila, S. Joshna.
May 2024 - Vol 12, Issue 3
Dr. P.A. Nageswara Rao, Mr. V. D. S. Venkat, Mrs. K. Sharmila, Mrs. M. Tharangini.
May 2024 - Vol 12, Issue 3
Ramana Babu Ch, Harish Kumar Yediri, Manohar Eere.
May 2024 - Vol 12, Issue 3
