FPGA-based Personal Authentication Using Fingerprints

Abstract

The current technological age demands the deployment of biometric security systems not only in those stringent and highly reliable fields (forensic, government, banking, etc.) but also in a wide range of daily use consumer applications (internet access, border control, health monitoring, mobile phones, laptops, etc.) accessible worldwide to any user. In order to succeed in the exploitation of biometric applications over the world, it is needed to make research on powerefficient and cost-effective computational platforms able to deal with those demanding image and signal operations carried out in the biometric processing. The present work deals with the evaluation of alternative system architectures to those existing PC (personal computers), HPC (high-performance computing) or GPU-based (graphics processing unit) platforms in one specific scenario: the physical implementation of an AFAS (automatic fingerprint-based authentication system) application. The development of automated fingerprint-based personal recognition systems in the way of compute-intensive and real-time embedded systems under SoPC (system-on-programmable-chip) devices featuring one general-purpose MPU (microprocessor unit) and one run-time reconfigurable FPGA (field programmable gate array) proves to be an efficient and cost-effective solution. The provided flexibility, not only in terms of software but also in terms of hardware thanks to the programmability and run-time reconfigurability performance exhibited by the suggested FPGA device, permits to build any application by means of hardware-software co-design techniques. The parallelism and acceleration performances inherent to the hardware design and the ability of reusing hardware resources along the application execution time are key factors to improve the performance of existing systems.

An Efficient Reconfigurable Architecture for Fingerprint Recognition

“…(b) In [47] authors proposed a solution of fingerprint recognition using a combination of ARM and FPGA. The use of full FPGA reconfiguration in our proposed method using Virtex 5 with SRAM is better in speed compared to reconfiguration latencies achieved using a combination of ARM and FPGA (EPXA10 DDR).…”

On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

“…We have used the minutiae-based fingerprint matching technique [23] using ridge counting. Given two sets of minutiae from the template (T) and the input fingerprint (I) images, the matching algorithm compares the minutiae points in the two images and returns a degree of similarity.…”

An energy efficient OpenCL implementation of a fingerprint verification system on heterogeneous mobile device

“…Mariano Fons, et al [11], implemented the first FPGA based fingerprint verification system application. This dynamically partial self reconfigurable FPGA, which contains abundant computing resources and embedded application specific integrated circuits (ASIC), is powerful enough to support the complicated computation for a completet fingerprint identification system.…”

“…Based on these achievements, various fingerprint verification systems have been successfully developed, adopting a wide range of platforms, such as CPUs, FPGAs [10], ASICs [1], and DSPs [15] as well.…”