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Bimodal Biometric Person Authentication System Using Speech and Signature Features
Eshwarappa M.N., Dr. Mrityunjaya V.Latte
Pages - 147 - 160     |    Revised - 30-08-2010     |    Published - 30-10-2010
Volume - 4   Issue - 4    |    Publication Date - September 2010  Table of Contents
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KEYWORDS
Speaker recognition, Signature verification, Multimodal biometrics, Biometrics
ABSTRACT
Biometrics offers greater security and convenience than traditional methods of person authentication. Multi biometrics has recently emerged as a means of more robust and efficient person authentication scheme. Exploiting information from multiple biometric features improves the performance and also robustness of person authentication. The objective of this paper is to develop a robust bimodal biometric person authentication system using speech and signature biometric features. Speaker based unimodal system is developed by extracting Mel Frequency Cepstral Coefficients (MFCC) and Wavelet Octave Coefficients of Residues (WOCOR) as feature vectors. The MFCCs and WOCORs from the training data are modeled using Vector Quantization (VQ) and Gaussian Mixture Modeling (GMM) techniques. Signature based unimodal system is developed by using Vertical Projection Profile (VPP), Horizontal Projection Profile (HPP) and Discrete Cosine Transform (DCT) as features. A bimodal biometric person authentication system is then built using these two unimodal systems. Experimental results show that the bimodal person authentication system provides higher performance compared with the unimodal systems. The bimodal system is finally evaluated for its robustness using the noisy data and also data collected from the real environments. The robustness of the bimodal system is more compared to the unimodal person authentication systems.
CITED BY (15)  
1 Zuva, T., Esan, O. A., & Ngwira, S. M. (2014). Hybridization of Bimodal Biometrics for Access Control Authentication. International Journal of Future Computer and Communication, 3(6), 444.
2 Hossain, S. E. (2014). Investigating Adaptive Multi-modal Approaches for Person Identity Verification Based on Face and Gait Fusion.
3 Kaur, G., Singh, D., & Kaur, S. (2014, October). Pollination based optimization for feature reduction at feature level fusion of speech & signature biometrics. In Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions), 2014 3rd International Conference on (pp. 1-6). IEEE.
4 Esan, O. A., Zuva, T., Ngwira, S., & Masupa, L. mitigating face biometric on electronic medical record.
5 Qureshi, K. (2013). Face-Gait Biometrics usage in Identity Verification.
6 Abbadi, L. (2012). Multi-factor Authentication Techniques for Video Applications over the Untrusted Internet (Doctoral dissertation, University Of Ottawa).
7 Alford, A., Bryant, K., Abagez, T., Dozier, G. V., Kelly, J. C., Shelton, J., ... & Ricanek, K. (2012). Genetic and evolutionary methods for biometric feature reduction. International Journal of Biometrics, 4(3), 220-245.
8 Ravi, J., & Raja, K. B. Concatenation of Spatial and Transformation Features for Off-Line signature Identification. International Journal of Innovative Technology and Exploring Engineering, 1, 102-108.
9 Hossain, S. M. E., & Chetty, G. (2011). Human Identity Verification by Using Physiological and Behavioural Biometric Traits. International Journal of Bioscience, Biochemistry and Bioinformatics, 1(3), 199.
10 Alford, A., Hansen, C., Dozier, G. V., Bryant, K. S., Kelly, J., Abegaz, T., ... & Woodard, D. L. (2011, June). GEC-based multi-biometric fusion. In IEEE Congress on Evolutionary Computation (pp. 2071-2074).
11 S. M. E. Hossain abd G. Chetty,, “Human Identity Verification by Using Physiological and Behavioural Biometric Traits”, International Journal of Bioscience, Biochemistry and Bioinformatics, 1(3), pp. 199-205, September 2011.
12 E. Hossain and G. Chetty , “Person Identity Verification Based on Multimodal Face-Gait Fusion”, International Journal of Computer Science and Network Security, 11(6), pp. 77-86, June 2011.
13 Chetty, G., & Singh, M. Information Fusion for Identity Verification.
14 S.M.E. Hossain, G. Chetty ,(2011), “Next Generation Identity Verification Based on Face-Gait Biometrics” in Proceedings of International Conference on Biomedical Engineering and Technology(ICBET 2011) Kuala Lumpur, Malaysia. June 17-19, 2011.
15 A. Alford, K. Popplewell,G. Dozier, K. Bryant, J. Kelly, J. Adams, T. Abegaz and J. Shelton, “GEFeWS: A Hybrid Genetic-Based Feature Weighting and Selection Algorithm for Multi-Biometric Recognition”, in Proceedings of The 22nd Midwest Artificial intelligence and Cognitive Science Conference (MAICS), 2011.
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Professor Eshwarappa M.N.
Sri siddharth Institute of Technology-Tumkur - India
jenutc@rediffmail.com
Professor Dr. Mrityunjaya V.Latte
JSS Academy of Technical Education-Bangalore - India


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