Multimodal Biometric Authentication Systems Using Convolution Neural Network Based on Different Level Fusion of ECG and Fingerprint

Multimodal Biometric Authentication Systems Using Convolution Neural Network Based on Different Level Fusion of ECG and Fingerprint

A multimodal biometric system integrates information from more than one biometric modality to improve the performance of each individual biometric system and make the system robust to spoof attacks. In this paper, we propose a secure multimodal biometric system that uses convolution neural network (...

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Bibliographic Details
Main Authors: Mohamed Hammad, Yashu Liu, Kuanquan Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Authentication
CNN
decision fusion
ECG
feature fusion
fingerprint
Online Access:https://ieeexplore.ieee.org/document/8575133/

Internet

https://ieeexplore.ieee.org/document/8575133/

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