Volume 2, Issue 5, September 2017, Page: 51-65
Product of Likelihood Ratio Scores Fusion of Face, Speech and Signature Based FJ-GMM for Biometrics Authentication Application Systems
SOLTANE MOHAMED, Electrical Engineering & Computing Department, Faculty of Sciences & Technology, Doctor Yahia Fares University of Medea, Medea, Algeria
Received: May 3, 2017;       Accepted: Jul. 10, 2017;       Published: Aug. 1, 2017
DOI: 10.11648/j.mcs.20170205.11      View  2370      Downloads  180
The paper proposes a likelihood ratio fusion of face, voice and signature multimodal biometrics verification application systems. Figueiredo-Jain (FJ) estimation algorithm of finite Gaussian mixture modal (GMM) is employed. Automated biometric systems for human identification measure a “signature” of the human body, compare the resulting characteristic to a database, and render an application dependent decision. These biometric systems for personal authentication and identification are based upon physiological or behavioral features which are typically distinctive, Multi-biometric systems, which consolidate information from multiple biometric sources, are gaining popularity because they are able to overcome limitations such as non-universality, noisy sensor data, large intra-user variations and susceptibility to spoof attacks that are commonly encountered in mono modal biometric systems. Simulation show that finite mixture modal (GMM) is quite effective in modelling the genuine and impostor score densities, fusion based the resulting density estimates achieves a significant performance on eNTERFACE 2005 multi-modal database based on face, signature and voice modalities.
Gaussian Mixture Modal, Figueiredo-Jain, Biometrics Face Recognition, Speaker and Signature Verification Systems, Score Fusion, Likelihood Ratio
To cite this article
SOLTANE MOHAMED, Product of Likelihood Ratio Scores Fusion of Face, Speech and Signature Based FJ-GMM for Biometrics Authentication Application Systems, Mathematics and Computer Science. Vol. 2, No. 5, 2017, pp. 51-65. doi: 10.11648/j.mcs.20170205.11
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
S. Gleni and P. Petratos, DNA Smart Card for Financial Transactions, The ACM Student Magazine 2004, http://www.acm.org.
G. Chetty and M. Wagner, Audio-Visual Multimodal Fusion for Biometric Person Authentication and Liveness Verification, Australian Computer Society, Inc. This paper appeared at the NICTA-HCSNet Multimodal UserInteraction Workshop (MMUI2005), Sydney, Australia.
N. Poh and S. Bengio, Database, Protocol and Tools for Evaluating Score-Level Fusion Algorithms in Biometric Authentication, IDIAP RR 04-44, August 2004, a IDIAP, CP 592, 1920 Martigny, Switzerland.
S. K. Sahoo and S. R. Mahadeva Prasanna, Bimodal Biometric Person Authentication Using Speech and Face Under Degraded Condition, National Conference on Communication (NCC), Bangalore - India, IEEE Xplore 17 March 2011.
D. Kaur, G. kaur and D. Singh, Efficient and Robust Multimodal Biometric System for Feature Level Fusion (Speech and Signature), International Journal of Computer Applications (0975 – 8887) Volume 75– No.5, August 2013.
S. Chaudhary and R. Nath, A New Multimodal Biometric Recognition System Integrating Iris, Face and Voice, International Journal of Advanced Research in Computer Science and Software Engineering, (ISSN: 2277 128X), Volume 5, Issue 4, April 2015.
Girija M. K. and Sowmya K. S., Multi-Biometric Person Authentication System Using Speech, Signature and Handwriting Features, The International Journal Of Engineering And Science (IJES), Volume 3 - Issue 6, Pages 68-74, 2014.
M. Anusha and T. V. Vamsi Krishna, Multimodal Biometric System Integrating Fingerprint Face and Iris, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 10, October 2016.
P. S. Sanjekar and J. B. Patil, An Overview of Multimodal Biometrics, Signal & Image Processing: An International Journal (SIPIJ) Vol.4, No.1, February 2013.
Mandeep Kaur, Akshay Girdhar and Manvjeet Kaur, Multimodal Biometric System Using Speech and Signature Modalities, International Journal of Computer Applications (IJCA) Volume 5– No.12, August 2010.
Corradini, M. Mehta, N. O. Bernsen, J. C. Martin, S. Abrilian, MULTIMODAL INPUT FUSION IN HUMAN- COMPUTER INTERACTION, On the Example of the NICE Project 2003; Natural Interactive Systems Laboratory (NISLab), University of Southern Denmark, DK-Odense M, Denmark. Laboratory of Computer Science for Mechanical and Engineering Sciences, LIMSI-CNRS, F-91403 Orsay, France. Montreuil Computer Science Institute (LINC-IUT), University Paris 8, F-93100 Montreuil, France.
Y. Zana, Roberto M. Cesar-Jr, Rogerio S. Feris, and Matthew Turk, Face Verification in Polar Frequency Domain: A Biologically Motivated Approach, G. Bebis et al. (Eds.): ISVC 2005, LNCS 3804, pp. 183–190, 2005. C_Springer-Verlag Berlin Heidelberg 2005 - Dept. of Computer Science, IME-USP, Brazil, University of California, Santa Barbara.
M. Turk and A. Pentland, Eigenfaces for Recognition, Journal of Cognitive Neuroscience, vol. 3, no. 1, pp. 71-86, 1991.
Pekka Paalanen, Bayesian classification using gaussian mixcute model and EM estimation: implementation and comparisons, Information Technology Project, 2004, Lappeenranta, June 23, 2004, http://www.it.lut.fi/project/gmmbayes/
C. Sanderson, S. Bengio, H. Bourlard, J. Mariéthoz, R. Collobert, Mohamed F. BenZeghiba, F. Cardinaux, and S. Marcel, “SPEECH & FACE BASED BIOMETRIC AUTHENTICATION AT IDIAP”, Dalle Molle Institute for Perceptual Artificial Intelligence (IDIAP). Rue du Simplon 4, CH-1920 Martigny, Switzerland.
C. Vielhauer, S. Schimke, V. Thanassis , Y. Stylianou, Otto-von-Guericke University Magdeburg, Universitaetsplatz 2, D-39106, Magdeburg, Germany, University of Crete, Department of Computer Science, Heraklion, Crete, Greece, Fusion Strategies for Speech and Handwriting Modalities in HCI, Multimedia on Mobile Devices, edited by Reiner Creutzburg, Jarmo H. Takala, Proc. of SPIE-IS&T Electronic Imaging, Vol. 5684 © 2005.
Lasse L Mølgaard and Kasper W Jørgensen, Speaker Recognition: Special Course, IMM_DTU December 14, 2005
S. Davis and P. Mermelstein. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Transactions on Acoustics, Speech and Signal Processing, (4):357–366, 1980.
D. A. Reynolds, Experimental Evaluation of Features for Robust Speaker Identification, IEEE Trans. Speech and Audio Processing 2-(4), 1994, 639-643.
M. SOLTANE, N. DOGHMANE, N. GUERSI. State of the Art: Signature Biometrics Verification, BRAIN. Broad Research in Artificial Intelligence and Neuroscience. Vol 1, N 2, Romania 2010. http://www.edusoft.ro/brain
M. SOLTANE, B. MIMEN, Soft Decision Level Fusion Approach to a Combined Behavioral Speech Signature Biometrics Verification, International Journal of Signal Processing, Image Processing and Pattern Recognition – IJSIP, Vol.5, No. 5 South Korea (March 2013). http://www.sersc.org/journals/IJSIP/vol5_no5.php
J. Richiardi, J. Fierrez-Aguilar, J. Ortiga-Garcia and A. Drygajlo, On-line Signature Verification Resilience to Packet Loss in IP Networks. Second COST 275 Workshop Biometrics on the Internet: Fundamentals, Advances and Applications. University of Vigo, Vigo-Spain 25-26 March 2004.
K. Veeramachaneni, L. Ann Osadciw, and P. K. Varshney, An Adaptive Multimodal Biometric Management Algorithm, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS-PART C: APPLICATIONS AND REVIEWS, VOL. 35, NO. 3, AUGUST 2005.
Van Trees, Harry L., Detection, Estimation, and Modulation Theory, Part I, John Wiley and Sons, 1968.
Qing Yan and Rick S. Blum, Distributed Signal Detection under the Neyman-Pearson Criterion, EECS Department Lehigh University Bethlehem, PA 18015.
K. Nandakumar, Y. Chen, Sarat C. Dass and Anil K. Jain, Likelihood Ratio Based Biometric Score Fusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007.
P. Paalanen, J.-K. Kamarainen, J. Ilonen, H. Kälviäinen, Feature Representation and Discrimination Based on Gaussian Mixture Model Probability Densities: Practices and Algorithms, Department of Information Technology, Lappeenranta University of Technology, P. O. Box 20, FI-53851 Lappeenranta, Finland 2005.
J. Kittler, M. Hatef, Robert P. W. Duin, and J. Matas, On Combining Classifiers, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 20, NO. 3, MARCH 1998.
Van Trees, Harry L., Detection, Estimation, and Modulation Theory, Part I, John Wiley and Sons, 1968.
Qing Yan and Rick S. Blum, Distributed Signal Detection under the Neyman-Pearson Criterion, EECS Department Lehigh University Bethlehem, PA 18015.
Yannis S., Yannis P., Felipe C., Pedro L., Francois S., Sascha S., Rolando B., Federico M., and Athanasios V., GMM-Based Multimodal Biometric Verification, eNTERFACE 2005 The summer Workshop on Multimodal Interfaces July 18th – August 12th, Facultè Polytechnique de Mons, Belgium.
Browse journals by subject