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A.Haritha Deepthi, S.Nithin Kalirajan, S.V. Thirupathi


As the Person‟s/Organization‟s Private information‟s are becoming very easy to access, the demand for a Simple, Convenient, Efficient, and a highly Securable Authentication System has been increased. In considering these requirements for data Protection, Biometrics, which uses human physiological or behavioral system for personal Identification has been found as a solution for these difficulties. However most of the biometric systems have high complexity in both time and space. So we are going to use a Real time Finger-Vein recognition System for authentication purposes. In this paper we had implemented the Finger Vein Recognition concept using MATLAB R2013a. The features used are Lacunarity Distance, Blanket Dimension distance. This has more accuracy when compared to conventional methods.

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A. K. Jain, S. Pankanti, S. Prabhakar, H. Lin, and A. Ross, “Biometrics: a grand challenge”, Proceedings of the 17th International Conference onPattern Recognition (ICPR), vol. 2, pp. 935-942, 2004. [2] P. Corcoran and A. Cucos, “Techniques for securing multimedia content in consumer electronic appliances using biometric signatures,” IEEE Transactionson Consumer Electronics, vol 51, no. 2, pp. 545-551, May 2005.

Y. Kim, J. Yoo, and K. Choi, “A motion and similarity-based fake detection method for biometric face recognition systems,” IEEE Transactions on Consumer Electronics, vol.57, no.2, pp.756-762, May 2011.

D. Wang , J. Li, and G. Memik, “User identification based on fingervein patterns for consumer electronics devices”, IEEE Transactions on Consumer Electronics, vol. 56, no. 2, pp. 799-804, 2010.

H. Lee, S. Lee, T. Kim, and Hyokyung Bahn, “Secure user identification for consumer electronics devices,” IEEE Transactions on Consumer 9+Electronics, vol.54, no.4, pp.1798-1802, Nov. 2008.

D. Mulyono and S. J. Horng, “A study of finger vein biometric for personal identification”, Proceedings of the International Symposium Biometrics and Security Technologies, pp. 134-141, 2008.

. Anil K. Jain, Patrick Flynn, and Arun A. Ross. Handbook of Biometrics. Springer-Verlag, USA, 2007.

. W. O. Jungbluth. Knuckle print identification. Journal of Forensic Identification, 39:375– 380, 1989.

. A. Kumar and C. Ravikanth. Personal authentication using finger knuckle surface. IEEE Transactions on Information Forensics and Security, 4(1):98 –110, 2009.

. A. Kumar and Y. Zhou. Personal identification using finger knuckle orientation features. Electronics Letters, 45(20):1023 –1025, 2009.

. David G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60:91–110, 2004.

. Krystian Mikolajczyk and Cordelia Schmid. A performance evaluation of local descriptors. IEEE Transaction Pattern Analysis Machine Intelligence, 27:1615–1630, October 2005.



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