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A fast fusion technique for fingerprint and iris spatial descriptors in multimodal biometric systems

机译:一种多模式生物特征识别系统中指纹和虹膜空间描述符的快速融合技术

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摘要

Multimodal biometric identification systems aim to combine two or more physical or behavioral traits to provide optimal False Acceptance Rate (FAR) and False Rejection Rate (FRR). In this paper a new fusion technique for fingerprint and iris spatial descriptors with a low execution time is presented. The report focuses on spatial fusion strategies, offering and proposing a modern perspective on multi-biometrics. In greater detail, a spatial-based approach and a homogeneous biometric vector, integrating iris and fingerprint data, are generated, fused, and processed for the overall system matching score. The goal of this approach is to demonstrate that, by using spatial iris features following the standard fingerprint approaches (faster and easier to extract with considerable saving execution time), the recognition system can sustain a comparable robust level with respect to literature frequency based approaches. The resulting multimodal system achieves interesting performance with several commonly used databases, in terms of both accuracy rate and authentication time. As an example, an interesting working point with FAR = 0% and FRR = 7.07%÷9.64% has been obtained, by using the well-known BATH database and the FVC2002 DB2A database. The biometric trait processing time requires 6.44 Sec on a general purpose computer.
机译:多模式生物特征识别系统旨在结合两个或多个身体或行为特征,以提供最佳的错误接受率(FAR)和错误拒绝率(FRR)。本文提出了一种新的融合技术,用于指纹和虹膜空间描述符的执行时间短。该报告侧重于空间融合策略,提供并提出了关于多生物计量学的现代观点。更详细地,生成,融合和处理基于虹膜和指纹数据的基于空间的方法和同质生物特征向量,以用于整体系统匹配分数。该方法的目标是证明,通过使用遵循标准指纹方法的空间虹膜特征(更快,更容易提取,并节省了大量执行时间),识别系统可以相对于基于文献频率的方法保持相当的鲁棒水平。最终的多峰系统在准确率和身份验证时间方面都可以通过几个常用的数据库实现有趣的性能。例如,通过使用众所周知的BATH数据库和FVC2002 DB2A数据库,获得了FAR = 0%和FRR = 7.07%÷9.64%的有趣工作点。生物特征处理时间在通用计算机上需要6.44 Sec。

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