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Development of Multimodal Biometric Systems with Three-Way and Fuzzy Set-Based Decision Mechanisms

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Abstract

Owing to well-documented advantages, multimodal biometrics systems form one of the visible and promising trends in the development of biometric systems. The results produced by the multimodal biometric system come as the aggregation of results produced by individual modalities encountered in the problem. In verification systems involving a single modality, a threshold has to be identified to separate the yes–no regions of the biometrics decision. However, in multimodal verification, there are four regions separated by two thresholds. In this paper, we introduce a concept of three-valued logic in a multimodal verification system in which four thresholds and nine regions have to be identified. The thresholds (regions) are optimized for a given number of parameters. Different structures of multimodal biometrics are tested for synthetic and publicly available datasets.

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References

  1. Jain, A., Ross, A., Pankanti, S.: Biometrics: a tool for information security. IEEE Trans. Inf. Forensics Secur. 1(2), 125–143 (2006)

    Article  Google Scholar 

  2. Marinoff, L.: The Middle Way, Finding Happiness in a World of Extremes. Sterling, New York (2007)

    Google Scholar 

  3. Łukasiewicz, J.: Philosophical remarks on many-valued systems of propositional logic. In: Borkowski, L. (ed.) Selected Works, pp. 481–495. North-Holland, Amsterdam (1970)

    Google Scholar 

  4. Lang, C., Steinbach, B.: Bi-decomposition of function sets in multiple-valued logic for circuit design and data mining. Artif. Intell. Rev. 20(3–4), 233–267 (2003)

    Article  MATH  Google Scholar 

  5. Bing, Z., Yiyu, Y., Jigang, L.: Cost-sensitive three-way email spam filtering. Intell. Inf. Syst. 42(1), 19–45 (2014)

    Article  Google Scholar 

  6. Miller, D., Thornton, M.: Multiple Valued Logic: Concepts and Representations. Synthesis Lectures on Digital Circuits and Systems. Morgan & Claypool Publishers, San Rafael (2008)

    Google Scholar 

  7. Vatankhahghadim, A., Sheikholeslami, A.: A multi-level cell for STT-MRAM with biaxial magnetic tunnel junction. In: Proceedings of IEEE International Symposium on Multiple-Valued Logic, pp. 158–163 (2015)

  8. Koob, J., Ung, S., Cockburn, B., Elliott, D.: Design and characterization of a multilevel DRAM. IEEE Trans. Very Large Scale (VLSI) Syst. 19(9), 1583–1596 (2011)

    Article  Google Scholar 

  9. Yao, Y.: Decision-theoretic rough set models. In: Proceedings of RSKT’07, LNAI 4481, pp. 1–12 (2007)

  10. Yao, Y.: Three-way decision: an interpretation of rules in rough set theory. In: Proceedings of RSKT’09, LNAI 5589, pp. 642–649 (2009)

  11. Yao, Y., Zhao, Y.: Attribute reduction in decision-theoretic rough set models. Inf. Sci. 178(17), 3356–3373 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  12. Yao, Y.: Three-way decisions with probabilistic rough sets. Inf. Sci. 180(3), 341–353 (2010)

    Article  MathSciNet  Google Scholar 

  13. Tahayori, H., Sadeghian, A., Pedrycz, W.: Induction of shadowed sets based on the gradual grade of fuzziness. IEEE Trans. Fuzzy Syst. 21, 937–949 (2013)

    Article  Google Scholar 

  14. Pedrycz, W.: Shadowed sets: representing and processing fuzzy sets. IEEE Trans. Syst. Man Cybern. Part B 28, 103–109 (1998)

    Article  Google Scholar 

  15. Zhou, J., Pedrycz, W., Miao, D.: Shadowed sets in the characterization of rough-fuzzy clustering. Pattern Recogn. 44(8), 1738–1749 (2011)

    Article  Google Scholar 

  16. Sahoo, S., Choubisa, T., Prasanna, S.: Multimodal biometric person authentication: a review. IETE Tech. Rev. 29(1), 54–75 (2012)

    Article  Google Scholar 

  17. Deng, X.F., Yao, Y.Y., Yao, J.T.: On interpreting three-way decisions through two-way decisions. In: ISMIS 2014, LNCS (LNAI), vol. 8502, pp. 73–82 (2014)

  18. Yao, Y.Y.: An outline of a theory of three-way decisions. In: RSCTC 2012. LNCS (LNAI), vol. 7413, pp. 1–17 (2012)

  19. Peters, G., Weber, R.: DCC: a framework for dynamic granular clustering. Granul. Comput. 1(1), 1–11 (2016)

    Article  Google Scholar 

  20. Livi, L., Sadeghian, A.: Granular computing, computational intelligence, and the analysis of non-geometric input spaces. Granul. Comput. 1(1), 13–20 (2016)

    Article  Google Scholar 

  21. Xu, Z., Wang, H.: Managing multi-granularity linguistic information in qualitative group decision making: an overview. Granul. Comput. 1(1), 21–35 (2016)

    Article  Google Scholar 

  22. Antonelli, M., Ducange, P., Lazzerini, B., Marcelloni, F.: Multi-objective evolutionary design of granular rule-based classifiers. Granul. Comput. 1(1), 37–58 (2016)

    Article  Google Scholar 

  23. Mendel, J.M.: A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of a linguistic term for computing with words. Granul. Comput. 1(1), 59–69 (2016)

    Article  Google Scholar 

  24. Lingras, P., Haider, F., Triff, M.: Granular meta-clustering based on hierarchical, network, and temporal connections. Granul. Comput. 1(1), 71–92 (2016)

    Article  Google Scholar 

  25. Skowron, A., Jankowski, A., Dutta, S.: Interactive granular computing. Granul. Comput. 1(2), 95–113 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  26. Dubois, D., Prade, H.: Bridging gaps between several forms of granular computing. Granul. Comput. 1(2), 115–126 (2016)

    Article  Google Scholar 

  27. Loia, V., D’Aniello, G., Gaeta, A., Orciuoli, F.: Enforcing situation awareness with granular computing: a systematic overview and new perspectives. Granul. Comput. 1(2), 127–143 (2016)

    Article  Google Scholar 

  28. Yao, Y.: A triarchic theory of granular computing. Granul. Comput. 1(2), 145–157 (2016)

    Article  Google Scholar 

  29. Ciucci, D.: Orthopairs and granular computing. Granul. Comput. 1(3), 159–170 (2016)

    Article  Google Scholar 

  30. Wilke, G., Portmann, E.: Granular computing as a basis of human–data interaction: a cognitive cities use case. Granul. Comput. 1(3), 181–197 (2016)

    Article  Google Scholar 

  31. Liu, H., Gegov, A., Cocea, M.: Rule-based systems: a granular computing perspective. Granul. Comput. 1(4), 259–274 (2016)

    Article  Google Scholar 

  32. Deng, X., Yao, Y.: Decision-theoretic three-way approximations of fuzzy sets. Inf. Sci. 279, 702–715 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  33. Liang, D., Liu, D., Pedrycz, W., Hu, P.: Triangular fuzzy decision-theoretic rough sets. Int. J. Approx. Reason. 54(8), 1087–1106 (2013)

    Article  MATH  Google Scholar 

  34. Sang, Y., Liang, J., Qian, Y.: Decision-theoretic rough sets under dynamic granulation. Knowl. Based Syst. 91, 84–92 (2016)

    Article  Google Scholar 

  35. Bromek, T., Niewiadomska-Bugaj, M.: Threshold rules in two-class discrimination problems. Probab. Math. Stat. 8, 11–16 (1987)

    MathSciNet  MATH  Google Scholar 

  36. Yeung, D.Y., Chang, H., Xiong, Y., George, S., Kashi, R.,Matsumoto, T., Rigoll, G.: SVC 2004: first international signature verification competition. In: Proceedings of the International Conference on Biometric Authentication, LNCS, vol. 3072, pp. 16–22 (2004)

  37. Bellman, R.: Dynamic Programming. Princeton University Press, Princeton (1957)

    MATH  Google Scholar 

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Acknowledgements

This project was funded by the National Plan for Science, Technology and Innovation (MAARIFAH)—King Abdulaziz City for Science and Technology—the Kingdom of Saudi Arabia—Award Number (12-INF3105-03). The authors also acknowledge with thanks Science and Technology Unit, King Abdulaziz University for technical support.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Rami Al-Hmouz, Witold Pedrycz, Khaled Daqrouq & Ali Morfeq

  2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, T6R 2V4, Canada

    Witold Pedrycz

Authors
  1. Rami Al-Hmouz
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  2. Witold Pedrycz
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  3. Khaled Daqrouq
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  4. Ali Morfeq
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Correspondence to Rami Al-Hmouz.

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Al-Hmouz, R., Pedrycz, W., Daqrouq, K. et al. Development of Multimodal Biometric Systems with Three-Way and Fuzzy Set-Based Decision Mechanisms. Int. J. Fuzzy Syst. 20, 128–140 (2018). https://doi.org/10.1007/s40815-017-0299-9

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  • DOI: https://doi.org/10.1007/s40815-017-0299-9

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