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Comparative Analysis of Multimodal Biometric System


Affiliations
1 Department of Computer Science, G.I.M.E.T , Amritsar, Punjab, India
2 Department Computer Science, G.I.M.E.T , Amritsar, Punjab, India
 

Networked environment provides legion of resources but also causing uncertainties due to crimes like computer hacking, illegal access of ATM and cell phone, security is the prime requirement. To overcome this barrier, biometric techniques are used as authentication technique to prevent unauthorized access. Biometric system kind of a method to scrutinize exclusive physical or behavioural traits to determine individual's identity. In this study ,providing the review comparison multimodal biometric system which provide additional accuracy as compared to unimodal biometric systems. The system of concern takes the input either from single or multiple sources and verifies it against the historical information stored within the dataset. This technology uses more than one biometric identifier to compare the identity of the individual. Thus, the system uses three technologies i.e. face, mimic along voice and if any one of this technology is not able to identify, the system scan still use the other two to get accurate results. The main objective of this paper is to use fusion of these biometric techniques for performance enhancement, security , minimize the system error rates to achieve better results.

Keywords

Biometric, Multimodal Biometric, Security, Sensors.
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  • This, P. (n.d.). Chapter 5 Genetic Algorithm ( Ga ) for Facial Biometric Security System ( Bss ), 79–109.

  • Hotta, K., Member, S., & Mishima, T. (2001). Scale Invariant Face Detection and Classification Method Using Shift Invariant Features Extracted from Log-Polar. IEEE Transactions on Information Systems, E84-D(7), 867–878.

  • Aggarwal, A.,&Verma, M.K.(2016).Multimodal Biometric Systems – A Survey. International Journal of Advanced Research in Computer Science and Software Engineering, 6(3), 437–441.

  • Ahuja, M. S., & Chabbra, S. (n.d.). A Survey of Multimodal Biometrics. International Journal of Computer Science and Its Applications, 157–160.

  • Anwar, R. W., Bakhtiari, M., Zainal, A., Abdullah, A. H., Qureshi, K. N., Computing, F., & Bahru, J. (2014). Security Issues and Attacks in Wireless Sensor Network. World Applied Sciences Journal, 30(10), 1224–1227. http://doi.org/10.5829/idosi.wasj.2014.30.10.334

  • Gopal, N., & Selvakumar, R. K. (2016). Multimodal Biometric Identification System - An Overview. International Journal of Engineering Trends and Technology (IJETT), 33(7), 351–355.

  • Jabbar, M. A., Deekshatulu, B. L., & Chandra, P. (2013). Classification of Heart Disease Using K- Nearest Neighbor and Genetic Algorithm. Procedia Technology, 10, 85–94. http://doi.org/10.1016/j.protcy.2013.12.340

  • Karaboga, D., Aslan, S., & O, U. N. O. O. O. U. N. U. U. N. (n.d.). A New Emigrant Creation Strategy for Parallel Artifissscial Bee Colony Algorithm ØÒ ××, 689–694.

  • Mane, P. V. M. (n.d.). Review of Multimodal Biometrics : Applications , challenges and Research Areas, 3(5), 90–95.

  • National Science and Technology Council Subcommittee on Biometrics. (2006). Face Recognition.

  • Noorjahan Khatoon, M. K. G. (2013). Multimodal Biometrics: A Review. IRACST - International Journal of Computer Science and Information Technology & Security(IJCSITS), ISSN: 2249-9555 Vol. 3, No.3, June 2013, 3(3), 230–236.

  • Panchal, T. (2013). Multimodal Biometric System. International Journal of Advanced Research in Computer Science and Software Engineering, 3(5), 1360–1363.

  • Shaikh, J. (2016). Review of Hand Feature of Unimodal and Multimodal Biometric System. International Journal of Computer Applications, 133(5), 19–24[

  • Meenakshi sharma and Dr. Himanshu Aggarwal,“EHR Adoption in India: Potential and the Challenges”, Indian Journal of Science and Technology,2016.

  • Tashtarian, F., Yaghmaee Moghaddam, M. H., Sohraby, K., & Effati, S. (2015). On Maximizing the Lifetime of Wireless Sensor Networks in Event-Driven Applications With Mobile Sinks. IEEE Transactions on Vehicular Technology, 64(7), 3177–3189. http://doi.org/10.1109/TVT.2014.2354338

  • Yang, X., & Hossein Gandomi, A. (2012). Bat algorithm: a novel approach for global engineering optimization. Engineering Computations, 29(5), 464–483. http://doi.org/10.1108/02644401211235834


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  • Comparative Analysis of Multimodal Biometric System

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Authors

Gagandeep Kaur
Department of Computer Science, G.I.M.E.T , Amritsar, Punjab, India
Samandeep Singh
Department Computer Science, G.I.M.E.T , Amritsar, Punjab, India
Navneet Kaur
Department of Computer Science, G.I.M.E.T , Amritsar, Punjab, India

Abstract


Networked environment provides legion of resources but also causing uncertainties due to crimes like computer hacking, illegal access of ATM and cell phone, security is the prime requirement. To overcome this barrier, biometric techniques are used as authentication technique to prevent unauthorized access. Biometric system kind of a method to scrutinize exclusive physical or behavioural traits to determine individual's identity. In this study ,providing the review comparison multimodal biometric system which provide additional accuracy as compared to unimodal biometric systems. The system of concern takes the input either from single or multiple sources and verifies it against the historical information stored within the dataset. This technology uses more than one biometric identifier to compare the identity of the individual. Thus, the system uses three technologies i.e. face, mimic along voice and if any one of this technology is not able to identify, the system scan still use the other two to get accurate results. The main objective of this paper is to use fusion of these biometric techniques for performance enhancement, security , minimize the system error rates to achieve better results.

Keywords


Biometric, Multimodal Biometric, Security, Sensors.

References