Biometrics means technology of measuring and analyzing physiological or biological characteristics of living body for identification and verification purposes. A biometric system provides automatic recognition of an individual based on some sort of unique feature or characteristic of the individual. Biometric systems is based on palmprints, fingerprints, facial features, voice, signature, hand features, handwriting, the retina and iris. User verification systems that use a single biometric indicator often have to contend with noisy sensor data, restricted degree of freedom, non-universality of the biometric modalities and unacceptable error rates. So the need of modifying multimodal biometric system occurred. A multimodal biometric system have different biometric traits and provides better recognition performance as compared to the systems based on single biometric trait. This paper presents a review of multibiometric systems including its recognition technologies, level of fusion and feature extraction for fingerprint and iris. Features like minutia points from fingerprint and texture from iris are extracted.

1. Jain, A. K. , Ross, A. , Prabhakar, S. : An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics 14 (2004) 4-20
2. Jain, A. K. , Ross, A. : Multibiometric Systems. Communications of the ACM, Special Issue on Multimodal Interfaces 47 (2004) 34-40
3. H. C. Lee, & R. E. Gaensslen, Eds. , Advances in Fingerprint Technology (New York, Elsevier, 1991).
4. Federal Bureau of Investigation, The Science of Fingerprints (Classification and Uses) (Washington, D. C. , US Govt. Printing Office, 1984).
5. C. Sanderson, and K. K. Paliwal, "Noise compensation in a person verification system using face and multiple speech features", Pattern recognition, Vol. 2, 2003, pp. 293-302.
6. S. S. Iyengar, L. Prasad, and H. Min, Advances in Distributed Sensor Technology, Prentice Hall, 1995.
7. R. Singh, M. Vatsa, A. Ross, and A. Noore, "Performance Enhancement of 2D Face Recognition via Mosaicing", in Proceedings of the 4th IEEE Workshop on Automatic Identification Advanced Technologies (AuotID), 2005, pp. 63–68.
8. A. Ross, and R. Govindarajan, "Feature Level Fusion Using Hand And Face Biometrics", in Proceedings of SPIE Conference on Biometric Technology for Human Identification, Vol. 5779, 2005, pp. 196–204.
9. A. K. Jain, K. Nandakumar, U. Uludag, and X. Lu, "Multimodal Biometrics", from Augmenting Face With Other Cues, in W. Zhao, and R. Chellappa, (eds) Face Processing: Advanced Modelling and Methods, Elsevier, New York, 2006. pp. 675-705.
10. A. Jaina, K. Nandakumara, A. Ross, and A. Jain, "Score Normalization in Multimodal Biometric Systems", Journal of Pattern Recognition, Vol. 38, 2005, pp. 2270.
11. A. K. Jain, and A. Ross, "Multibiometric Systems. Communications of The ACM", Special Issue on Multimodal Interfaces, Vol. 47, No. 1, 2004, pp. 34-40.
12. M. X. He, S. J. Horng, P. Z. Fan, R. S. Run, R. J. Chen, J. L. Lai, M. K. Khan and K. O. Sentosa, "Performance Evaluation of Score Level Fusion in Multimodal Biometric Systems", Journal of Pattern Recognition, Vol. 43, No. 5, 2010, pp. 1789-1800.
13. A. Ross, and A. K. Jain, "Fusion Techniques in Multibiometric Systems", from Face Biometrics for Personal Identification. In. R. I. Hammound, B. R. Abidi and M. A. Abidi (eds. ), Publisher Springer Berlin Heidelberg, 2007, pp. 185-212.
14. PhukeV. A, H. N. Bharathi, "Information Retrieval using Dempster-Shafer Theory" International Journal of Computer Applications (0975 – 8887) Volume 102– No. 13, September 2014.
15. R. Brunelli, and D. Falavigna, "Person Identification Using Multiple Cues", IEEE Transactions on Pattern Analysis and Machine.
16. Intelligence, Vol. 17, No. 10, 1995, pp. 955–966. C. C. Lip, and D. A. Ramli, "Comparative Study on Feature, Score and decision Level Fusion Schemes for Robust Multibiometric Systems", Advances in Intelligent and Soft Computing, Vol. 133, 2012, pp. 941-948.

Biometrics multimodal fingerprint iris recognitiontechniques level Of Fusion And Feature Extraction Of Iris And Fingerprints.