A statistical approach towards performance analysis of multimodal biometric systems

Xiaobu Yuan, Wei Gan
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引用次数: 7

Abstract

This paper investigates the application of statistical methods in performance analysis of multimodal biometric systems. It develops an efficient and systematic approach to evaluate system performance under the influence of errors. Based upon the proposed approach, 126 experiments are conducted with the BSSR1 dataset on typical fusion methods using different normalization techniques. Experiment results demonstrate that the Simple Sum fusion method yields the best overall performance when working with Min-Max normalization. More importantly, further examination of experimental results reveals the need for systematic analysis of system performance as the performance of some fusion methods may exhibit big variations when the level of errors changes, and some fusion methods may produce very good performance in some application though normally unacceptable in others.
多模态生物识别系统性能分析的统计方法
本文研究了统计方法在多模态生物识别系统性能分析中的应用。它开发了一种有效的、系统的方法来评估系统在误差影响下的性能。基于该方法,在BSSR1数据集上对不同归一化技术的典型融合方法进行了126次实验。实验结果表明,简单和融合方法在处理最小-最大归一化时具有最佳的综合性能。更重要的是,对实验结果的进一步检查表明,需要对系统性能进行系统分析,因为当误差水平发生变化时,某些融合方法的性能可能会表现出很大的变化,并且某些融合方法可能在某些应用中产生非常好的性能,尽管在其他应用中通常不可接受。
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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