Multimodal biometric authentication

Authors

  • Lokeswara Rao Bhogadi 1 1 Profeesor & HOD, Dept. of ECE, CMR College of Engineering & Technology
  • N. Bhagyalaxmi 2 2 Assistant professor, Dept. of ECE,CMR College of Engineering & Technology

DOI:

https://doi.org/10.18063/wct.v2i1.417

Keywords:

Iris, finger print and palm images, MATLAB software

Abstract

In the present era of information technology, there is a need to implement authentication and authorization techniques for security of resources. There are number of ways to prove authentication and authorization. But the biometric authentication beats all other techniques. Biometric techniques prove the authenticity or authorization of a human being based on his/her physiological or behavioural traits. Biometrics is a technique by which an individual's identity can be authenticated by applying the physical or behavioural trait. Physical traits like fingerprints, palm, iris etc. are based on the physical characteristics which are generally inherent and unique. Behavioural traits like voice, signature or keystroke dynamics etc. on the other hand, are quantifiable characteristics.They also protect access of resources from unauthorized users. Multimodal biometrics refers to the use of a combination of two or more biometric modalities in a verification / identification system. Identification based on multiple biometrics represents an emerging trend. The most compelling reason to combine different modalities is to improve the recognition rate. This can be done when biometric features of different biometrics are statistically independent. A multimodal biometric identification system aims to fuse two or more physical or behavioural traits. Multimodal biometric system is used in order to improve the accuracy. Multimodal biometric identification system based on iris, palm and fingerprint trait based on fusion logic is proposed. Typically in a multimodal biometric system, each biometric trait processes its information independently. The processed information is combined using curve let transform.

References

Jain AK, Ross A. Multibiometric systems. Communications of the ACM 2004; 47(1): 34-40.

Ross A, Jain AK. Information fusion in biometrics. Pattern Recognition Letters 2003; 24 (13): 2115–2125.

Huber PJ, Statistics R (John Wiley & Sons, 1981).

Snelick R, Indovina M, Yen J, et al. Mink multimodal biometrics: issues in design and testing, in proceedings of fifth international conference on multimodal interfaces. 2003: 68–72.

Indovina M, Uludag U, Snelick R, et al. Combining COTS finger and face biometrics for identity verification, in Proceedings of Workshop on MultiModal User Authentication 2003: 99-106.

Downloads

Published

2018-08-30

Issue

Section

Original Research Articles