Abstract

Biometrics methods of human identification have gained much attention recently, mainly because they easily deal with most problems of traditional identification, since users are identified by who they are, not by something they have to remember or carry with them. This paper attempts to improve the performance of signature based authentication system by cascading orthogonal transforms. The signatures are acquired using WACOM digital pen tablet and then features are extracted. Our experimental results on the image data set from 75 users, confirm the advantages of our cascaded approach over unimodal approaches. It should be noted that a distinct advantage of the proposed system is that it does not require multiple signature samples for training.

References

• Anil K. Jain, Arun Ross and Salil Prabhakar, “An Introduction to Biometric Recognition”, IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics, Vol. 14, No. 1, January 2004.
• Sulochana Sonkamble, Ravindra Thool , Balwant Sonkamble, “Survey of Biometric Recognition Systems and their applications”, Journal of Theoretical and Applied Information Technology 2005 - 2010.
• Payman Moallem1, Seyed Amirhassan Monadjemi, “Dynamic Online Signatures Recognition using a novel Signature base normalized feature string and MLP Neural Network” , Iranian Journal of Engineering sciences , Vol.1, No.1,2007.
• Lin Hong and Anil Jain, “Integrating Faces and Fingerprints for Personal Identification”, IEEE Transactions on Pattern Analysis and Machine Intelligence”, Vol.20, No.12, December 1998.
• Arun Ross, Anil Jain, “Information fusion in biometrics”, Pattern Recognition Letters 24 (2003) 2115–2125.
• Ning – Ning Liu, Yun-Hong Wang, “Fusion of Global and Local information for an online Signature Verification system”, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, 12-15 July 2008.
• WACOM Bamboo Digital Pen Tablet, www.wacom.co.in /bamboo, June 2011.
• S. Jayaraman, S Esakkirajan, T Veerakumar, “Digital Image Processing”, by Mc Graw Hill, 2008.
• Rafael C. Gonzalez, Richard E. Woods, ‘Digital Image Processing’, 9th Edition, Prentice Hall, New York, Sept 09.
• Vaishali Kulkarni, H. B. Kekre, “Comparative Analysis of Automatic Speaker Recognition using Kekre’s Fast Codebook GeneratioAlgorithm in Time and Transform Domain”, International Journal of Computer Applications Volume 7– No.1, September 2010 pp-37-41.
• Xin Pan , Qiuqi Ruan1 , Yanxia Wang, “Palm print Recognition using Fusion of Local and Global features”, Proceedings of 2007 International Symposium on Intelligent Signal Processing and Communication Systems Nov.28-Dec.1, 2007 .
• Aman Chadha, Divya Jyoti, M. Mani Roja, “Rotation, Scaling and Translation Analysis of Biometric Signature Templates”, Int. J. Comp. Tech. Appl., Vol 2 (5), 1419-1425, Sept 2011.
• Mehfuza Holia, V.K Thakur, “ Image Registration for recovering Affine Transformation using Nelder Mead Simplex method for optimization”, International Journal of Image Processing (IJIP) Volume(3), Issue(5).
• G. Wolberg and S. Zokai, “Robust Image Registration Using Log-Polar Transform”, Proceedings of the IEEE International Conference on Image Processing, Sep. 2000.
• Z. Y. Cohen, “Image registration and object recognition using affine invariants and convex hulls”, IEEE Transactions on Image Processing, July 1999, pp. 1-3.
• N. Chumchob and K. Chen, “A Robust Affine Image Registration Method”, International Journal of Numerical Analysis and Modeling, Volume 6, Number 2,2009, pp. 311-334.