An Overview on Multi-biometric Score-level Fusion - Verification and Identification

Naser Damer, Alexander Opel, Andreas Shahverdyan


Multi-biometrics is the use of multiple biometric recognition sources to provide a more dependable verification or identification decision. Fusion of multi-biometric sources can be performed on different levels, such as the data, feature, or score level. This work presents an overview of the multi-biometric score-level fusion problem, along with the proposed solution in the literature. A discussion is made to provide a comparison between multi-biometric fusion in both scenarios. This discussion aims at providing a clearer view of future developments especially under the identification scenario where many related applications are rapidly growing such as forensics and ubiquitous surveillance.


  1. Alsaade, F. (2010). A study of neural network and its properties of training and adaptability in enhancing accuracy in a multimodal biometrics scenario. Information Technology Journal.
  2. Arandjelovic, O. and Hammoud, R. (2006). Multi-sensory face biometric fusion (for personal identification). In Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop, CVPRW 7806, pages 128-, Washington, DC, USA. IEEE Computer Society.
  3. Baig, A., Bouridane, A., Kurugollu, F., and Qu, G. (2009). Fingerprint - iris fusion based identification system using a single hamming distance matcher. In Proceedings of the 2009 Symposium on Bio-inspired Learning and Intelligent Systems for Security, BLISS 7809, pages 9-12, Washington, DC, USA. IEEE Computer Society.
  4. Basak, J., Kate, K., Tyagi, V., and Ratha, N. (2010). A gradient descent approach for multi-modal biometric identification. In Pattern Recognition (ICPR), 2010 20th International Conference on, pages 1322 -1325.
  5. Cappelli, R., Maio, D., and Maltoni, D. (2000). Combining fingerprint classifiers. In Proceedings of the First International Workshop on Multiple Classifier Systems, MCS 7800, pages 351-361, London, UK, UK. Springer-Verlag.
  6. Chang, K., Bowyer, K. W., Sarkar, S., and Victor, B. (2003). Comparison and combination of ear and face images in appearance-based biometrics. IEEE Trans. Pattern Analysis and Machine Intelligence, 25:1160-1165.
  7. Chang, K. I., Bowyer, K. W., Flynn, P. J., and Chen, X. (2004). Multi-biometrics using facial appearance, shape and temperature. In Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition, FGR' 04, pages 43-48, Washington, DC, USA. IEEE Computer Society.
  8. Cheng, X., Tulyakov, S., and Govindaraju, V. (2011). Multiple-sample fusion of matching scores in biometric systems. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on, pages 120 -125.
  9. De Marsico, M., Nappi, M., Riccio, D., and Tortora, G. (2011). Nabs: Novel approaches for biometric systems. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 41(4):481 -493.
  10. Dinerstein, S., Dinerstein, J., and Ventura, D. (2007). Robust multi-modal biometric fusion via multiple svms. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Montral, Canada, 7-10 October 2007, pages 1530-1535. IEEE.
  11. Garcia-salicetti, S., Mellakh, M. A., Allano, L., and Dorizzi, B. (2005). Multimodal biometric score fusion: The mean rule vs. support vector classifiers. In Proceedings of the EUSIPCO.
  12. Hariri, M. and Shokouhi, S. B. (2012). Robustness of multi biometric authentication systems against spoofing. Computer and Information Science, pages 77-86.
  13. Ichino, M., Komatsu, N., Wang, J.-G., and You, W. Y. (2010). Speaker gender recognition using score level fusion by adaboost. In 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010, Singapore, 7-10 December 2010, Proceedings, pages 648-653. IEEE.
  14. Islam, M. R. and Rahman, M. F. (2010). Article:likelihood ratio based score fusion for audio-visual speaker identification in challenging environment. International Journal of Computer Applications, 6(7):6-11. Published By Foundation of Computer Science.
  15. Jain, A., Nandakumar, K., and Ross, A. (2005). Score normalization in multimodal biometric systems. Pattern Recogn., 38(12):2270-2285.
  16. Jin, A. T. B., Samad, S. A., and Hussain, A. (2004). Nearest neighbourhood classifiers in a bimodal biometric verification system fusion decision scheme. Journal of Research and Practice in Information Technology, 36(1):47-62.
  17. K. Nandakumar, A. K. J. and Ross, A. (2009). Fusion in multibiometric identification systems: What about the missing data? In Proceedings of the 3rd International Conference on Biometrics, Alghero, Italy.
  18. Kim, Y., Toh, K.-A., and Teoh, A. (2010). An online learning algorithm for biometric scores fusion. In Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on, pages 1 -6.
  19. L. Latha, S. T. (2011). On improving the performance of multimodal biometric authentication through ant colony optimization. WSEAS Transactions on Information Science and Applications.
  20. Mehrotra, H., Vatsa, M., Singh, R., and Majhi, B. (2012). Biometric match score fusion using rvm: A case study in multi-unit iris recognition. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on, pages 65 -70.
  21. Moin, M. S. and Parviz, M. (2009). Exploring auc boosting approach in multimodal biometrics score level fusion. In Proceedings of the 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 7809, pages 616-619, Washington, DC, USA. IEEE Computer Society.
  22. Moreno, B., Sanchez, A., and Velez, J. (1999). On the use of outer ear images for personal identification in security applications. In Security Technology, 1999. Proceedings. IEEE 33rd Annual 1999 International Carnahan Conference on, pages 469 -476.
  23. Nandakumar, K., Chen, Y., Dass, S. C., and Jain, A. (2008). Likelihood ratio-based biometric score fusion. IEEE Trans. Pattern Anal. Mach. Intell., 30(2):342-347.
  24. Nandakumar, K., Chen, Y., Jain, A. K., and Dass, S. C. (2006). Quality-based score level fusion in multibiometric systems. In Proceedings of the 18th International Conference on Pattern Recognition - Volume 04, ICPR 7806, pages 473-476, Washington, DC, USA. IEEE Computer Society.
  25. Nisha Srinivas, Kalyan Veeramachaneni, L. O. (2009). Fusing correlated data from multiple classifiers for improved biometric verification. In 12th International Conference on Information Fusion.
  26. Phillips, P., Flynn, P., Beveridge, J., Scruggs, W., OToole, A., Bolme, D., Bowyer, K., Draper, B., Givens, G., Lui, Y., Sahibzada, H., Scallan, JosephA., I., and Weimer, S. (2009). Overview of the multiple biometrics grand challenge. In Tistarelli, M. and Nixon, M., editors, Advances in Biometrics, volume 5558 of Lecture Notes in Computer Science, pages 705-714. Springer Berlin Heidelberg.
  27. Poh, N. and Bengio, S. (2006). Database, protocols and tools for evaluating score-level fusion algorithms in biometric authentication. Pattern Recogn., 39(2):223- 233.
  28. Poh, N., Bourlai, T., and Kittler, J. (2010a). A multimodal biometric test bed for quality-dependent, costsensitive and client-specific score-level fusion algorithms. Pattern Recogn., 43(3):1094-1105.
  29. Poh, N. and Kittler, J. (2008). A family of methods for quality-based multimodal biometric fusion using generative classifiers. In ICARCV, pages 1162-1167. IEEE.
  30. Poh, N., Merati, A., and Kittler, J. (2009). Making better biometric decisions with quality and cohort information: A case study in fingerprint verification. In Proc. 17th European Signal Processing Conf. (Eusipco), pages 70-74, Glasgow.
  31. Poh, N., Windridge, D., Mottl, V., Tatarchuk, A., and Eliseyev, A. (2010b). Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. Trans. Info. For. Sec., 5(3):461- 469.
  32. Rattani, A., Kisku, D. R., Bicego, M., and Tistarelli, M. (2006). Robust Feature-Level Multibiometric Classification. Biometric Consortium Conference, 2006 Biometrics Symposium: Special Session on Research at the, pages 1-6.
  33. Rodríguez, L. P., Crespo, A. G., Lara, M. J. P., and Mezcua, B. R. (2008). Study of different fusion techniques for multimodal biometric authentication. In Proceedings of the 2008 IEEE International Conference on Wireless & Mobile Computing, Networking & Communication, WIMOB 7808, pages 666-671, Washington, DC, USA. IEEE Computer Society.
  34. Singh, R., Vatsa, M., and Noore, A. (2007). Intelligent biometric information fusion using support vector machine. In Nachtegael, M., Van der Weken, D., Kerre, E., and Philips, W., editors, Soft Computing in Image Processing, volume 210 of Studies in Fuzziness and Soft Computing, pages 325-349. Springer Berlin Heidelberg.
  35. Tong, Y., Wheeler, F., and Liu, X. (2010). Improving biometric identification through quality-based face and fingerprint biometric fusion. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on, pages 53 -60.
  36. Vajaria, H., Islam, T., Mohanty, P., Sarkar, S., Sankar, R., and Kasturi, R. (2007). Evaluation and analysis of a face and voice outdoor multi-biometric system. Pattern Recogn. Lett., 28(12):1572-1580.
  37. Wang, Y., Tan, T., and Jain, A. (2003). Combining face and iris biometrics for identity verification. In Kittler, J. and Nixon, M., editors, Audio- and Video-Based Biometric Person Authentication, volume 2688 of Lecture Notes in Computer Science, pages 805-813. Springer Berlin Heidelberg.
  38. Yan, P. (2006). Ear biometrics in human identification. PhD thesis, University of Notre Dame, Notre Dame, IN, USA. AAI3406950.
  39. Yan, P. and Bowyer, K. W. (2005). Multi-biometrics 2d and 3d ear recognition. In Kanade, T., Jain, A. K., and Ratha, N. K., editors, AVBPA, volume 3546 of Lecture Notes in Computer Science, pages 503-512. Springer.

Paper Citation

in Harvard Style

Damer N., Opel A. and Shahverdyan A. (2013). An Overview on Multi-biometric Score-level Fusion - Verification and Identification . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013) ISBN 978-989-8565-41-9, pages 647-653. DOI: 10.5220/0004358306470653

in Bibtex Style

author={Naser Damer and Alexander Opel and Andreas Shahverdyan},
title={An Overview on Multi-biometric Score-level Fusion - Verification and Identification},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013)},

in EndNote Style

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013)
TI - An Overview on Multi-biometric Score-level Fusion - Verification and Identification
SN - 978-989-8565-41-9
AU - Damer N.
AU - Opel A.
AU - Shahverdyan A.
PY - 2013
SP - 647
EP - 653
DO - 10.5220/0004358306470653