Fast and accurate biometric identification using score level indexing and fusion

Takao Murakami, Kenta Takahashi
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引用次数: 22

Abstract

Biometric identification provides a very convenient way to authenticate a user because it does not require the user to claim an identity. However, both the identification error rates and the response time increase almost in proportion to the number of enrollees. A technique which decreases both of them using only scores has the advantage that it can be applied to any kind of biometric system that outputs scores. In this paper, we propose such a technique by combining score level fusion and distance-based indexing. In order to reduce the retrieval error rate in multibiometric identification, our technique takes a strategy to select the template of the enrollee whose posterior probability of being identical to the claimant is the highest as a next to be matched. The experimental evaluation using the Biosecure DS2 dataset and the CASIA-FingerprintV5 showed that our technique significantly reduced the identification error rates while keeping down or even reducing the number of score calculations, compared to the unimodal biometrics.
使用分数水平索引和融合快速准确的生物特征识别
生物识别提供了一种非常方便的方式来验证用户,因为它不需要用户声明身份。然而,识别错误率和响应时间几乎与参保人数成正比。一种只使用分数来减少两者的技术的优势在于它可以应用于任何输出分数的生物识别系统。在本文中,我们提出了一种结合分数水平融合和基于距离的索引的技术。为了降低多生物特征识别中的检索错误率,我们的技术采用一种策略,选择与申请人相同的后验概率最高的登陆者模板作为下一个匹配。使用Biosecure DS2数据集和CASIA-FingerprintV5进行的实验评估表明,与单峰生物识别技术相比,我们的技术在降低甚至减少分数计算次数的同时显著降低了识别错误率。
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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