The week's pick
Random Articles
Reseach Article
Handwritten Signature Verification using Neural Network
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 2 |
| Year of Publication: 2012 |
| Authors: Ashwini Pansare, Shalini Bhatia |
10.5120/ijais12-450114
|
Ashwini Pansare, Shalini Bhatia . Handwritten Signature Verification using Neural Network. International Journal of Applied Information Systems. 1, 2 ( January 2012), 44-49. DOI=10.5120/ijais12-450114
Abstract
A number of biometric techniques have been proposed for personal identification in the past. Among the vision-based ones are face recognition, fingerprint recognition, iris scanning and retina scanning. Voice recognition or signature verification are the most widely known among the non-vision based ones. As signatures continue to play an important role in financial, commercial and legal transactions, truly secured authentication becomes more and more crucial. A signature by an authorized person is considered to be the “seal of approval” and remains the most preferred means of authentication. The method presented in this paper consists of image prepossessing, geometric feature extraction, neural network training with extracted features and verification. A verification stage includes applying the extracted features of test signature to a trained neural network which will classify it as a genuine or forged.
References
- Prasad A.G. Amaresh V.M. “An offline signature verification system”
- Prashanth CR,KB Raja,KR Venugopal, LM Patnaik,”Standard Scores Correlation based Offline signature verification system”, International Conference on advances in computing, control and telecommunication Technologies 2009
- 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.
- J Edson, R. Justino, F. Bortolozzi and R. Sabourin, "An off-line signature verification using HMM for Random,Simple and Skilled Forgeries", Sixth International Conference on Document Analysis and Recognition, pp.1031-1034, Sept.2001. 211-222, Dec.2000.
- J Edson, R. Justino, A. El Yacoubi, F. Bortolozzi and R. Sabourin, "An off-line Signature Verification System Using HMM and Graphometric features", DAS 2000
- B. Herbst. J. Coetzer. and J. Preez, “Online Signature Verification Using the Discrete Radon Transform and a Hidden Markov Model,” EURASIP.Journal on Applied Signal Processing, vol. 4, pp. 559–571, 2004.
- M. Blumenstein. S. Armand. and Muthukkumarasamy, “Off-line Signature Verification using the Enhanced Modified Direction Feature and Neural based Classification,” International Joint Conference on Neural Networks, 2006.
- S.Srihari. K. M. Kalera. and A. XU, “Offline Signature Verification and Identification Using Distance Statistics,” International Journal of Pattern Recognition And Artificial Intelligence ,vol. 18, no. 7, pp. 1339–1360, 2004.
- H. S. Srihari and M. Beall, “Signature Verifcation Using Kolmogrov Smirnov Statistic,”Proceedings of International Graphonomics Society,Salemo Italy , pp. 152–156, june,2005.
- T.S. enturk. E. O¨ zgunduz. and E. Karshgil, “ Handwritten Signature Verification Using Image Invariants and Dynamic Features,” Proceedings of the 13th European Signal Processing Conference EUSIPCO 2005,Antalya Turkey, 4th-8th September, 2005.
- Ramachandra A. C ,Jyoti shrinivas Rao”Robust Offline signature verification based on global features” IEEE International Advance Computing Conference ,2009.
- Martinez, L.E., Travieso, C.M, Alonso, J.B., and Ferrer, M. Parameterization of a forgery Handwritten Signature Verification using SVM. IEEE 38thAnnual 2004 International Carnahan Conference on Security Technology ,2004 PP.193-196
Index Terms
Keywords