Abstract
Biometric systems based on a single biometric trait have drawbacks that are alleviated by multibiometric systems, which combine multiple sources of information. The novelty of this research effort is that Coalition Game Theory (CGT) is applied to improve the performance of the iris and face based multibiometric system. The CGT technique selects the most salient patches obtained using the Local Binary Patterns (LBP) and modified LBP (mLBP) feature extraction techniques. The CGT chooses patches that have better individual importance along with a strong interaction with other patches based on the Shapely value. Results show that CGT model maintains impressive recognition accuracy while using smaller image areas for recognition. More specifically, CGT outperforms the LBP and mLBP techniques.
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Acknowledgements
This research was funded by the National Science Foundation (NSF) and Science & Technology Center: Bio/Computational Evolution in Action Consortium (BEACON).
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Aljohani, N., Ahmad, F., Roy, K., Shelton, J. (2015). Mutibiometric System Based on Game Theory. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_21
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DOI: https://doi.org/10.1007/978-3-319-20801-5_21
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