Faculty of Electronics Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdańsk, Poland.
Sensors (Basel). 2022 Mar 18;22(6):2356. doi: 10.3390/s22062356.
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.
本文对基于 Dempster-Shafer 理论(DST)及其修正的决策融合方法进行了评估,并在工程化多模态银行客户验证系统的真实生物识别数据上进行了研究。首先,解释了用于验证的多模态生物识别数据融合方法。然后提出了比较分数融合的实现方法,包括 DST 的应用、所需的修改、基本概率和质量转换的详细信息。接下来,描述了生物特征验证过程,并提供了工程生物特征银行系统的原理。最后,根据各种假设的阈值和生物特征验证技术,展示并讨论了三种融合方法在合成数据和真实数据上的验证结果,考虑到通过最小化错误拒绝率来实现期望的结果。