Multimodal biometrics: An overview

A. Ross, Anil K. Jain
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引用次数: 729

Abstract

Unimodal biometric systems have to contend with a variety of problems such as noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. Some of these limitations can be addressed by deploying multimodal biometric systems that integrate the evidence presented by multiple sources of information. This paper discusses the various scenarios that are possible in multimodal biometric systems, the levels of fusion that are plausible and the integration strategies that can be adopted to consolidate information. We also present several examples of multimodal systems that have been described in the literature.
多模态生物识别:概述
单峰生物识别系统必须应对各种问题,如噪声数据、类内变化、受限自由度、非普适性、欺骗攻击和不可接受的错误率。其中一些限制可以通过部署多模式生物识别系统来解决,该系统集成了多个信息来源提供的证据。本文讨论了在多模态生物识别系统中可能出现的各种情况,合理的融合水平以及可以采用的整合策略来巩固信息。我们还提出了几个文献中描述的多模态系统的例子。
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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