A Comparative Study on Fingerprint Matching Algorithms for EVM

D. Ashok Kumar¹ and T. Ummal Sariba Begum^1,

¹Department of Computer Science, Government Arts College, Trichy, India

Cite this paper:
D. Ashok Kumar and T. Ummal Sariba Begum. A Comparative Study on Fingerprint Matching Algorithms for EVM. Journal of Computer Sciences and Applications. 2013; 1(4):55-60. doi: 10.12691/jcsa-1-4-1

Abstract

In biometric system, the fingerprint recognition has been researched for the long period of time and it has shown the most promising future in the real world application. However, because of the complex distortions among the different impression of the same finger in real life, fingerprint recognition is still a challenging problem. Matching two fingerprints can be unsuccessful due to various reasons and also depends upon the method that is being used for matching. Electronic Voting Machine (EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Because biometric identifiers cannot be easily misplaced, forged, or shared, they are considered more reliable for person recognition than traditional token or knowledge based methods. In this paper, the authors are interested to compare three fingerprint matching algorithms by conducting the election using novel EVM. Based on the election result in terms of matching accuracy, time taken for matching, the best algorithm is found for novel EVM. The three matching techniques are direct matching, minutiae matching and matching based on Ratios of distance. We conducted the evaluation on the FVC-2000 datasets and the results were observed by conducting election with the help of these matching techniques and the best matching technique is found for novel EVM.

Keywords:
biometric fingerprint minutiae matching voting EVM

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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References:

[1]	Pankanti S., Prabhakar S., Jain A.K., On the individuality of fingerprints, IEEE Trans. Patter Anal. Mach. Intell. 24 (8) pp: 1010-1025, 2002.
[2]	Jain A.K., Hong L., Pankanti S., Bolle R., An identity-authentication system using fingerprints, Proc. IEEE 85 (9) pp: 1364-1388, 1997.
[3]	Jiang X., Yau W.Y., Fingerprint minutiae matching based on the local and global structures, Proceedings of the International Conference on Pattern Recognition, pp. 1038-1041, 2000.
[4]	Kovacs-Vajna Z.M., A fingerprint verification system based on triangular matching and dynamic time warping, IEEE Trans. Pattern Anal. Mach. Intel. 22 (11):1266-1276, 2000.
[5]	Saleh A.A., Adhami R.R., Curvature-based matching approach for automatic fingerprint identification, Proceedings of the Southeastern Symposium on System Theory, pp. 171-175, 2001.
[6]	Jain A.K., Prabhakar S., Hong L., Pankanti S., Filterbank-based fingerprint matching, IEEE Trans. Image Process. 9 (5): 846-859, 2000.
[7]	Jain A.K., Ross A., Prabhakar S., Fingerprint matching using minutiae and texture features, Proceedings of the International Conference on Image Processing, vol. 3, pp. 282-285, 2001.
[8]	Ceguerra A.V., Koprinska I., Integrating local and global features in automatic fingerprint verification, Proceedings of the International Conference on Pattern Recognition, vol. 3, pp. 347-350, 2002.
[9]	Xuejun Tan, Bir Bhanu, “Fingerprint matching by genetic, algorithms, Pattern Recognition Society. Published by Elsevier Ltd, 39 pp: 465-477, 2006.
[10]	Robert S. Germain, Andrea Califano, And Scott Colville, “Fingerprint Matching Using Transformation Parameter Clustering”, theme article, IEEE Computational Science & Engineering, 1997.
[11]	Gold S. and Rangarajan A., “A graduated assignment algorithm for graph matching,” IEEE Transactions on Pattern Analysis and Machine Intelligence., vol. 18, no.4, pp.377-388, 1996.
[12]	Hrechak A.K. and Mchugh J.A., “Automated Fingerprint Recognition using Structural Matching,” Pattern Recognition, vol. 23, pp. 893-904, 1990.
[13]	Eshera M. and Fu K.S., “A Similarity Measure between Attributed Relational Graphs for Image Analysis,” in Proceedings of the 7th International Conference on PatternRecognition, Montreal, P.Q., Canada, July 30-Aug 3 1984.
[14]	Ratha N.K, Pundit V.D, Bolle R.M, Vaish V., “Robust Fingerprint Authentication Using Local Structural Similarity,” Workshop on Applications of Computer Vision, pp: 29-34, 2000.
[15]	Ranade A. and Rosenfeld A., “Point Pattern Matching byRelaxation,” Pattern Recog., vol, no: 12, 2; pp: 269-275, 1993.
[16]	Ton J. and Jain A.K., “Registering landsat images bypoint matching,” IEEE Transactions on GeoSci. RemoteSensing, vol.27, pp. 642-651, May 1989.
[17]	Jain A.K., Hong L., Pankanti S. and Bolle R., “An identity authentication system using fingerprints,” Proc. IEEE,vol.85, pp. 1365-1388, Sept.1997.
[18]	Ölz W. and Kropatsch W.G., “Graph Representation of Fingerprint Topology,” Computer Vision - CVWW'04, Slovenien Pattern Recognition Society, pp. 51-58, 2004.
[19]	Chikkerur S., Cartwright A. N. and Govindaraju V., "Kplet and CBFS: A Graph based Fingerprint Representation and Matching Algorithm," ICB 2006.
[20]	Sanjay Kumar, Ekta Waliam., “Analysis of Electronic Voting System in Various Countries”, International Journal on Computer Science and Engineering (IJCSE)”, ISSN: 0975-3397 Vol. 3 No. 5 May 2011.
[21]	Meltemp Ballan, Ayhan Sakarya F. and Brian L. Evans, "A Fingerprint Classification Technique Using Directional Images", 1997..
[22]	Mercuri R.. “Electronic Vote Tabulation Checks and balances”, PhD thesis, University of Pennsylvania, Philadelphia, PA, Oct.2000.
[23]	“Ridges and Furrows-history and science of fingerprint identification technology and legal issues”.http://ridgeand.furrows.homestead.com/fingerprint.html
[24]	“Voting: What Is; What Could Be”, MIT Voting Technology Project, July 2001.
[25]	Ashok Kumar D., Ummal Sariba Begum T., “A Novel design of Electronic Voting System Using Fingerprint”, International Journal Of Innovative Technology & Creative Ngineering Vol.1 No.1, pp:12-19, January 2011.
[26]	Abinandhan Chandrasekaran, Dr.Bhavani Thuraisingham, “Fingerprint Matching Algorithm Based on Tree Comparison using Ratios of Relational Distances” Second International Conference on Availability, Reliability and Security (ARES'07), IEEE Computer society 2007.