Multimodal biometric systems based on different fusion levels of ECG and fingerprint using different classifiers

• Published in: Soft computing (Berlin, Germany) Vol. 24; no. 16; pp. 12599 - 12632
• Main Author: El_Rahman, Sahar A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2020; Springer Nature B.V
• Subjects: Artificial Intelligence; Biometrics; Classification; Classifiers; Computational Intelligence; Control; Decision trees; Electrocardiography; Engineering; Fingerprints; Law enforcement; Likelihood ratio; Mathematical Logic and Foundations; Mechatronics; Methodologies and Application; Neural networks; Performance evaluation; Physiology; Robotics; Standard error; Support vector machines; Classification algorithms; Features extraction; Fingerprint recognition system; Multimodal biometrics; ECG recognition system

Multimodal biometric system can be accomplished at different levels of fusion and achieve higher recognition performance than the unimodal system. This paper concerned to study the performance of different classification techniques and fusion rules in the context of unimodal and multimodal biometric...