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Biometrics-based consumer applications driven by reconfigurable hardware architectures

机译:由可重新配置的硬件体系结构驱动的基于生物识别的消费者应用程序

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摘要

Nowadays the development of automatic biometrics-based personal recognition systems is a reality in the current technological age. Not only those applications demanding stringent security levels but also many daily use consumer applications request the existence of high performance computational platforms in charge of recognizing the identity of an individual based on the analysis of his/her physiological or behavioural characteristics. The state of the art points out two main open problems in the implementation of such automatic applications: on the one hand, the needed improvement of the reliability level of the existing recognition systems in terms of accuracy, security and real-time performances; on the other hand, the cost reduction of those physical platforms in charge of the processing.This work addresses those limitations of current systems and aims at finding the proper system architecture to develop this kind of high-performance applications at low cost. Because of that, those existing solutions based on expensive multiprocessor systems like HPC (High Performance Computer), GPU (Graphics Processing Unit), or PC (Personal Computer) platforms need to be discarded, and instead of them embedded system solutions based on programmable logic devices are suggested in this work. The programmability performances of FPGA (Field Programmable Gate Array) devices together with the inherent parallelism of hardware design provide the needed flexibility to develop made-to-measure coprocessors in charge of accelerating those time-critical computational tasks. To address the cost of the system, dynamically reconfigurable FPGAs are suggested in this work. The scheduling of the recognition application into a series of mutually exclusive tasks, and the reutilization of those functional resources available in the FPGA by multiplexing different coprocessors in the same area along the application execution time allows reducing the size of the device and therefore its cost at the expense of the reconfiguration overhead.The hardware-software co-design of an AFAS (automatic fingerprint-based authentication system) under two different run-time reconfigurable platforms is presented as the proof of concept of the suggested architecture. The outstanding results achieved in this work pave the way for the implementation of biometric applications by means of run-time reconfigurable FPGAs.
机译:如今,基于自动生物识别的个人识别系统的开发已成为当前技术时代的现实。不仅那些要求严格安全级别的应用程序,而且许多日常使用的消费者应用程序都要求存在高性能计算平台,这些平台负责根据对他/她的生理或行为特征的分析来识别个人的身份。现有技术指出了在实现这种自动应用程序中的两个主要的开放性问题:一方面,需要在准确性,安全性和实时性能方面提高现有识别系统的可靠性水平;另一方面,降低了负责处理的物理平台的成本。这项工作解决了当前系统的那些限制,旨在找到合适的系统架构,以低成本开发这种高性能的应用程序。因此,那些基于昂贵的多处理器系统(如HPC(高性能计算机),GPU(图形处理单元)或PC(个人计算机)平台)的现有解决方案需要丢弃,而应取代基于可编程逻辑的嵌入式系统解决方案建议在这项工作中使用设备。 FPGA(现场可编程门阵列)设备的可编程性能以及硬件设计的固有并行性为开发量身定制的协处理器提供了所需的灵活性,以负责加速那些对时间要求严格的计算任务。为了解决系统成本,建议在这项工作中使用动态可重新配置的FPGA。将识别应用程序安排为一系列互斥的任务,并通过沿着应用程序执行时间在同一区域中多路复用不同的协处理器来复用FPGA中可用的功能资源,可以减小设备的尺寸,从而降低其成本。提出了两种不同运行时可重配置平台下的AFAS(基于指纹自动认证系统)的软硬件协同设计,作为所建议体系结构概念的证明。这项工作中取得的杰出成果为通过运行时可重新配置的FPGA实现生物识别应用程序铺平了道路。

著录项

  • 来源
    《Future generation computer systems》 |2012年第1期|p.268-286|共19页
  • 作者

    M. Fons; F. Fons; E. Canto;

  • 作者单位

    Development of Embedded Systems Research Group, Department of Electronic, Electrical and Automatic Control Engineering, Universitat Rovira i Virgili, Tarragona 43007, Spain;

    Development of Embedded Systems Research Group, Department of Electronic, Electrical and Automatic Control Engineering, Universitat Rovira i Virgili, Tarragona 43007, Spain;

    Development of Embedded Systems Research Group, Department of Electronic, Electrical and Automatic Control Engineering, Universitat Rovira i Virgili, Tarragona 43007, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    biometrics; real-time systems and embedded systems; special-purpose hardware; flexible hardware; run-time reconfigurable FPGA; hardware-software co-design;

    机译:生物识别;实时系统和嵌入式系统;专用硬件;灵活的硬件;运行时可重配置FPGA;软硬件协同设计;

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