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摘要翻译：
生物特征识别是测量和分析人体生物数据，从获取的数据中提取特征集合，并将其与数据库中的模板集进行比较的科学和技术。实验研究表明，单峰生物特征识别系统在性能和准确性方面存在诸多不足。多模态生物特征识别系统比单模态生物特征识别系统性能更好，也更复杂。我们使用最先进的商业现成(COTS)产品来检验多模态生物认证系统的准确性和性能。这里我们讨论指纹和人脸生物识别系统，决策和融合技术在这些系统中使用。我们还讨论了它们相对于单峰生物识别系统的优势。
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英文标题：
《Multimodal Biometric Systems - Study to Improve Accuracy and Performance》
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作者：
K.Sasidhar, Vijaya L Kakulapati, Kolikipogu Ramakrishna and
K.KailasaRao
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最新提交年份：
2010
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. Experimental studies show that Unimodal biometric systems had many disadvantages regarding performance and accuracy. Multimodal biometric systems perform better than unimodal biometric systems and are popular even more complex also. We examine the accuracy and performance of multimodal biometric authentication systems using state of the art Commercial Off- The-Shelf (COTS) products. Here we discuss fingerprint and face biometric systems, decision and fusion techniques used in these systems. We also discuss their advantage over unimodal biometric systems.
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PDF链接：
https://arxiv.org/pdf/1011.6220
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