An Efficient Learning Using Iris and Fingerprint Multi-Modal Biometirc Authentication System

Authors(2) :-Rupinder Kaur, Dr. Naresh Kumar Garg

Biometrics deals with the technical field for body dimensions and controls. It states various metrics related to characteristics of the human. Biometrics verification is used in processors as a method of access control. It deals with the identification of the individuals in clusters that are under investigation. Biometric are the unique, measurable features used to tag and describe entities. Biometric are often considered as physical versus behavioral features. Physical features are related to the form of the physique. Examples comprises of fingerprint, veins, recognition of face, palm pattern, hand, iris acknowledgement. Behavioral features are related to the shape of a person which are not limited to gait, and voice. Various researchers have invented the term performance metrics to define the latter discussion of biometrics. So this paper deals with the biometric fusion of iris and fingerprint which provides more security for the authentication of authentic individual and the performance will be evaluated in terms of false acceptance rate, false rejection rate and accuracy of the system.

Authors and Affiliations

Rupinder Kaur
Computer Science and Engineering CSE Department, MRSPTU, Bathinda, India
Dr. Naresh Kumar Garg
Computer Science and Engineering CSE Department, MRSPTU, Bathinda, India

Biometrics, Security, Classification, Iris, Fingerprint

  1. Prof. Jin-Xin, Shi, and Xiao-FengGu. "The comparison of iris recognition using principal component analysis, independent component analysis, and Gabor wavelets." Computer Science and Information Technology(ICCSIT), 2010 3rd IEEE International Conference on. Vol. 1. IEEE, 2010
  2. K. P. Hollingsworth, K. W. Bowyer and P. J. Flynn "Improved iris recognition through the fusion of hamming distance and fragile bit distance", IEEE Trans. Pattern Anal. Mach. Intel., vol. 33, no. 12, pp.2465 -2476 2011
  3. Kocer, H. Erdinc, and N.Allahverdi. "An efficient iris recognition system based on modular neural networks." Proceedings of the 9th WSEAS International Conference on Neural Networks. World Scientific and Engineering Academy and Society (WSEAS), 2008
  4. Kshamaraj, Gulmire, and Sanjay Ganorkar. "Iris Recognition Using Independent Component Analysis." International journal of emerging technology and advanced engineering 2.7 (2012): 433-437.
  5. K. Saminathan, M. Chithra Devi, and T. Chakravarthy. "Pair of Iris Recognition for Personal Identification Using Artificial Neural Networks." IJCSI International Journal of Computer Science (2012)
  6. Chaudhary, Sheetal, and Rajender Nath. "A Robust Multimodal Biometric System Integrating Iris, Face and Fingerprint using Multiple SVMs." International Journal of Advanced Research in Computer Science 7, no. 2 (2016).
  7. Meva, Divyakant T., and C. K. Kumbharana. "Design and evaluation of multimodal biometric system with fingerprint and face recognition." International Journal of Scientific and Research Publications 5, no. 4 (2015): 1-4.
  8. Hassan, Norsalina, Dzati Athiar Ramli, and Shahrel Azmin Suandi. "Fusion of Face and Fingerprint for Robust Personal Verification System." International Journal of Machine Learning and Computing 4, no. 4 (2014): 371
  9. Dandawate, Yogesh H., and Sajeeda R. Inamdar. "Fusion based multimodal biometric cryptosystem." In Industrial Instrumentation and Control (ICIC), 2015 International Conference on, pp. 1484-1489.IEEE, 2015.
  10. Kihal, Nassima, Salim Chitroub, and Jean Meunier. "Fusion of iris and palm print for multimodal biometric authentication." In Image Processing Theory, Tools and Applications (IPTA), 2014 4th International Conference on, pp. 1-6.IEEE, 2014.

Publication Details

Published in : Volume 3 | Issue 6 | July-August 2018
Date of Publication : 2018-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 405-408
Manuscript Number : CSEIT183659
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Rupinder Kaur, Dr. Naresh Kumar Garg, "An Efficient Learning Using Iris and Fingerprint Multi-Modal Biometirc Authentication System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 6, pp.405-408, July-August-2018.
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