Continuous Distribution Approximation and Thresholds Optimization in Serial Multi-Modal Biometric Systems
Keywords:
multi-modal biometrics, sequential fusion, multi-criteria optimization, continuous distribution approximationAbstract
Multi-modal biometric verification systems use information from several biometric modalities to verify an identity of a person. The false acceptance rate (FAR)
and false rejection rate (FRR) are metrics generally used to measure the performance of such systems.
In this paper, we first approximate the score distributions of both genuine users and impostors by continuous distributions. Then we incorporate the exact expressions of the distributions in the formulas for the expected values of both FAR and FRR for each matcher. In order to determine the upper and lower acceptance thresholds in the sequential multi-modal biometric matching, we further minimize the expected values of FAR and FRR for the entire processing chain. We propose a non-linear bi-objective programming problem whose objective functions are the two error probabilities. We analyze the efficient set of the bi-objective problem, and derive an efficient solution as a best compromise between the error probabilities. Replacing the least squares approximation of the score distributions by a continuous distribution
approximation, this approach modifies the method presented in Stanojević et al. [15] (doi: 10.1109/ICCCC.2016.7496752) (a).
The results of our experiments showed a good performance of the sequential multiple biometric matching system based on continuous distribution approximation and optimized thresholds.
(a)Reprinted (partial) and extended, with permission based on License Number
3938230385072 © [2016] IEEE, from "Computers Communications and Control (ICCCC), 2016 6th International Conference on".
References
Ehrgott, M. ; (2000); Multicriteria Optimization, Berlin, Germany: Springer-Verlag, ISBN 3-540-21398-8.
Filatovas, E.; Podkopaev, D.; Kurasova, O.; (2015), A Visualization Technique for Accessing Solution Pool in Interactive Methods of Multiobjective Optimization, International Journal of Computers Communications & Control, ISSN 1841-9836, 10:508-519.
Filip, F.G.; (2015); Book Review: "Biometric and Intelligent Decision Making Support", In- ternational Journal of Computers Communications and Control, ISSN 1841-9836, 10(6):952- 953.
Hong, L.; Jain, A.; (1998), Integrating faces and fingerprints for personal identification, IEEE Trans. Pattern Anal. Mach. Intell., ISSN: 0162-8828, 20(12):1295-1307. http://dx.doi.org/10.1109/34.735803
Kaklauskas, A.; (2015), Biometric and Intelligent Decision Making Support, Springer-Verlag, ISBN 978-3-319-13659-2. http://dx.doi.org/10.1007/978-3-319-13659-2
Kumar, A. ; Kumar, A.; (016), Adaptive management of multimodal biometrics fusion using ant colony optimization, Information Fusion, ISSN: 1566-2535, 32:49-63.
Maltoni, D.; Maio, D.; Jain, A.K.; Prabhakar, S.; (2003); Handbook of Fingerprint Recogni- tion, New York: Springer-Verlag, ISBN 978-1-84882-254-2.
Marcialis, G.L.; Mastinu, P.; Roli, F. (2010), Serial fusion of multi-modal biometric systems. In: Biometric Measurements and Systems for Security and Medical Applications (BIOMS), IEEE Workshop on, ISBN: 978-1-4244-6302-2, 1-7. http://dx.doi.org/10.1109/BIOMS.2010.5610438
Mehrotra, H.; . Singh, R; Vatsa, M.; Majhi, B.; (2016), Incremental Granular Relevance Vector Machine: A Case Study in Multimodal Biometrics, Pattern Recognition, ISSN: 0031- 3203, 56:63-76.
Pathak, M.; Srinivasu, N.; (2015), Analysis of multimodal biometric system based on level of fusion, International Journal of Inventive Engineering and Sciences, ISSN: 2319-9598, 3:8-11.
Pato, J.N.; Millett, L.I. (eds); (2010); Biometric Recognition - Challenges and Opportunities, The National Academies Press, ISBN: 978-0-309-14207-6.
Ross, A. ; Nandakumar, K.; Jain, A.K.; (2006); Handbook of multibiometrics, Springer, ISBN: 978-0-387-33123-2.
Sheena, S.; Sheena, M.; (2014), A study of multimodal biometric systems, International Journal of Research in Engineering and Technology, ISSN: 2321-7308, 3:93-98.
Snelick, R.; Uludag, U.; Mink,A.; Indovina, M.; Jain, A.; (2005), Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems, Pattern Analysis and Machine Intelligence, IEEE Transactions on, ISSN: 0162-8828, 27:450-455.
Stanojević, M. ; Milenković, I.; StarÄević, D.; Stanojević, B.; (2016), Optimization of thresholds in serial multimodal biometric systems, 2016 6th International Conference on Computers Communications and Control (ICCCC), ISBN: 978-1-5090-1735-5, 140-146.
Tulyakov, S. ; Li, J.; Govindaraju, V.; (2008), Enrolled Template Specific Decisions and Combinations in Verification Systems, Biometrics: Theory, Applications and Systems, 2008. BTAS 2008. 2nd IEEE International Conference on, Arlington, VA, 2008, ISBN: 978-1-4244- 2729-1, 1-7.
Villegas, M.; Paredes, R.; (2009), Score Fusion by Maximizing the Area under the ROC Curve", Pattern Recognition and Image Analysis, LNCS 5524, ISSN: 1054-6618, 473-480.
Zhang, Q.; Yin, Y.; Zhan, D.-C.; Peng, J.; (2014), A Novel Serial Multimodal Biometrics Framework Based on Semisupervised Learning Techniques, IEEE Transactions on Informa- tion Forensics and Security, ISSN: 1556-6013, 9:1681-1694.
Published
Issue
Section
License
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.
