Abstract
This paper proposed the use of multimodal score-level fusion as a means to improve the performance of multimodal verification. Different algorithms have been used to extract the features: LG for extracting FKP features, LPQ for extracting iris features, and PCA for extracting face features. Results indicate that the multimodal verification approach has gained higher performance than using any single modality. The biometric performance using score-level fusions under “Sum,” “Max,” and “Min” rules have been demonstrated in this paper.
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AlMahafzah, H., AlRawashdeh, M.Z. (2016). Performance of Multimodal Biometric Systems at Score Level Fusion. In: Zeng, QA. (eds) Wireless Communications, Networking and Applications. Lecture Notes in Electrical Engineering, vol 348. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2580-5_82
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DOI: https://doi.org/10.1007/978-81-322-2580-5_82
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