Fingerprint-based human authentication has shown great potential for civil, forensic and corporate security applications in recent years. For large-scale databases, the complexity of the identification system increases and implementing these systems on general-purpose sequential computing devices becomes challenging. Field Programmable Gate Array (FPGA) has demonstrated to be an efficient tool for the acceleration of computationally challenging applications by utilizing parallelism in the computations. In this study, an FPGA-based hardware accelerator is exploited to propose a fast and robust fingerprint identification solution that is based on a generalized minutiae neighbor based encoding and matching algorithm. The proposed FPGA implementation employs the Distributed RAM resources efficiently by using them as look-up tables for matching the encoded minutiae features. The proposed FPGA-based fingerprint matching system has the potential to match 2.75 million fingerprints per second while maintaining a low error rate. The proposed system can be deemed as an effective solution for Automated Fingerprint Identification Systems (AFIS) for large-scale applications.

近年来，基于指纹的人类身份验证在民用，法医和公司安全应用中显示出巨大潜力。对于大规模数据库，识别系统的复杂性增加，并且在通用顺序计算设备上实现这些系统变得具有挑战性。现场可编程门阵列（FPGA）已证明是通过在计算中利用并行性来加速具有计算挑战性的应用程序的有效工具。在这项研究中，基于FPGA的硬件加速器被利用来提出一种快速而健壮的指纹识别解决方案，该解决方案基于基于广义细节邻域的编码和匹配算法。所提出的FPGA实现通过将分布式RAM资源用作查找表来匹配编码的细节特征，从而有效地利用了分布式RAM资源。所提出的基于FPGA的指纹匹配系统有可能每秒匹配275万个指纹，同时保持较低的错误率。所提出的系统可以被认为是用于大规模应用的自动指纹识别系统（AFIS）的有效解决方案。