Decision Level Fusion Using t-Norms

M. Hanmandlu, J. Grover, V. Madasu
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引用次数: 1

Abstract

A multimodal biometric system employing the hand based modalities (i.e. palmprint, hand veins, and hand geometry) is developed. The proposed approach for the decision level fusion combines the decisions from these modalities using t-norms due to Hamacher, Yager, Weber, Schweizer and Sklar. These norms deal with the uncertainty and imperfection pervading the different sources of knowledge (error rates from different modalities). The proposed biometric system is quite computationally fast and outperforms the decision level fusion accomplished through the conventional rules (OR, AND) The experimental evaluation on a database of 100 users confirms the effectiveness of the decision level fusion. The preliminary results are encouraging in terms of the decision accuracy and computing efficiency.
基于t规范的决策级融合
开发了一种采用基于手的模式(即掌纹,手静脉和手几何)的多模式生物识别系统。所提出的决策层融合方法使用由Hamacher、Yager、Weber、Schweizer和Sklar提出的t规范将这些模式的决策结合起来。这些规范处理遍及不同知识来源的不确定性和不完全性(来自不同模式的错误率)。该系统计算速度快,优于传统规则(OR、and)实现的决策级融合。在100个用户数据库上的实验评估证实了决策级融合的有效性。初步结果在决策精度和计算效率方面令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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