A Coupling of Voice and Iris Based Multimodal Biometric System for Person Authentication

Authors

  • Kale Vk Dept. of Computer Science and Information Technology, Dr.Babasaheb Ambedkar Marathwada University, Aurangabad, (MS), India
  • Deshmukh PD MGM Dr.G.Y.Pathrikar College of Computer Science and Information Technology, Aurangabad, (MS), India

DOI:

https://doi.org/10.26438/ijcse/v6i11.3338

Keywords:

Multimodel, Voice, Iris, MFCC, Fusion

Abstract

Automatic human authentication by machine has been an active research area.This research work focus on development of Voice and Iris based Multimodal biometric system for human Authentication. The experimental work divided in three part, first and second part develop unimodel Voice and Iris biometric system and third experiment carried out for multimodal biometric fusion .we have achieve above form Multimodal biometric system results using KVKRG Voice and KVKR Iris database is FAR1.4% ,FRR 0.8%, Accuracy is 97.8%, ASV2015 voice and MMU Iris Database is FAR1.0% ,FRR 0.6%, Accuracy is 98.4% , Regional Voice Database and KVKR Iris database is FAR1.1% ,FRR 0.6%, Accuracy is 98.3%.

References

[1] Campbell J.P. and Jr. “Speaker recognition: A Tutorial” Proceeding of the IEEE. Vol 85, 1437- 1462 1997.

[2] DOUGLAS O’SHAUGHNESSY, “Interacting with Computers by Voice: Automatic Speech Recognition and Synthesis”, Proceedings of the IEEE, VOL. 91, NO. 9, September 2003, 00189219/03 2003 IEEE.

[3] L.V. Birgale and M.Kokare, ”Iris Recognition Using Discrete Wavelet Transform”, IEEE Proceedings of the International Conference on Digital Image Processing (ICDIP’09), 2009.

[4] Amir azizi, Hamid reza P, “Efficient iris recognition through improvement of feature extraction and subset selection,” international journal of computer science and information security,vol2,no 1 June 2009.

[5] Aloui, K., Naït-Ali, A., Fournier, R. and Naceur, S.,“Introduction to Iris Biometrics, in Signal and Image Processing for Biometrics”, 2012,John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118561911.ch6.

[6] Anil Jain, Karthik Nandakumara, Arun Ross, “Score normalization in multimodal biometric systems” Elsevier Journal of Pattern Recognition, Pattern Recognition 38 (2005) 2270 – 2285,2005.

[7] Kazi M.M. “Multimodal Biometric System Using Face and Signature: A score Level Fusion Approach “Advances in Computational Research, ISSN: 0975-3273 & E-ISSN: 0975-9085, Volume 4, Issue 1, 2012, pp.-99-103.

[8] Zhao F., Huang Q. and Gao W. (2006) IEEE Int. Conference on Acoustics, Speech and Signal Processing 2, 14-19.

[9] Ulery B., Fellner W., Hallinan P., Austin Hicklin, Watson C. Studies of Biometric Fusion report, National Institute of Standards and Technology, 1-14. (2006).

[10] Richard M.," Multimodal Biometric Human Recognition for Perceptual Human—Computer Interaction", IEEE, Vol. 40, No. 6, November 2010

Downloads

Published

2018-11-30
CITATION
DOI: 10.26438/ijcse/v6i11.3338
Published: 2018-11-30

How to Cite

[1]
V. K. Kale and P. D. Deshmukh, “A Coupling of Voice and Iris Based Multimodal Biometric System for Person Authentication”, Int. J. Comp. Sci. Eng., vol. 6, no. 11, pp. 33–38, Nov. 2018.

Issue

Vol. 6 No. 11 (2018): IJCSE November Edition

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.