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DPD-DFF: A dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases

机译:DPD-DFF:具有双指纹融合的双相分布式方案,可在大型数据库中快速准确地进行识别

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摘要

Nowadays, many companies and institutions need fast and reliable identification systems that are able to deal with very large databases. Fingerprints are among the most used biometric traits for identification. In the current literature there are fingerprint matching algorithms that are focused on efficiency, whilst others are based on accuracy. In this paper we propose a flexible dual phase identification method, called DPD-DFF, that combines two fingers and two matchers within a hybrid fusion scheme to obtain both fast and accurate results. Different alternatives are designed to find a trade-off between runtime and accuracy that can be further tuned with a single parameter. The experiments show that DPD-DFF obtains very competitive results in comparison with the state-of-the-art score fusion techniques, especially when dealing with large databases or impostor fingerprints. (C) 2016 Elsevier B.V. All rights reserved.
机译:如今,许多公司和机构需要能够处理超大型数据库的快速可靠的识别系统。指纹是最常用于识别的生物特征。在当前文献中,有一些指纹匹配算法专注于效率,而其他算法则基于准确性。在本文中,我们提出了一种灵活的双相识别方法,称为DPD-DFF,该方法在混合融合方案中结合了两个手指和两个匹配器,从而获得了快速而准确的结果。设计了不同的替代方案,以在运行时间和精度之间找到权衡,可以通过单个参数进一步调整。实验表明,与最新的分数融合技术相比,DPD-DFF获得了非常有竞争力的结果,尤其是在处理大型数据库或冒名顶替者指纹时。 (C)2016 Elsevier B.V.保留所有权利。

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