Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application

Sensors (Basel). 2022 Mar 18;22(6):2356. doi: 10.3390/s22062356.

Abstract

An evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application of DST, required modifications, base probability, and mass conversions. Next, the biometric verification process is described, and the engineered biometric banking system principles are provided. Finally, the validation results of three fusion approaches on synthetic and real data are presented and discussed, considering the desired outcome manifested by minimized false non-match rates for various assumed thresholds and biometric verification techniques.

Keywords: biometric sensors; biometric systems; biometry; data fusion; identity verification; multimodal biometrics.

MeSH terms

  • Biometry* / methods
  • Humans