FPGA-based embedded system implementation of finger vein biometrics

With the ubiquitous deployment and rapid growth of electronic information systems in today's society, personal or identity verification is now a critical key problem. Due to this fact, biometric authentication has emergently gaining popularity as it provides a high security and reliable approac...

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Bibliographic Details
Published in:2010 IEEE Symposium on Industrial Electronics and Applications pp. 700 - 705
Main Authors: Khalil-Hani, M, Eng, P C
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2010
Subjects:
Authentication
Biometric
Biometrics
Embedded System
Feature extraction
Finger Vein
Fingers
FPGA
Gray-scale
Pixel
RTOS
Veins
ISBN:1424476453, 9781424476459
Online Access:Get full text
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Summary:With the ubiquitous deployment and rapid growth of electronic information systems in today's society, personal or identity verification is now a critical key problem. Due to this fact, biometric authentication has emergently gaining popularity as it provides a high security and reliable approach for personal authentication. However, authentication using ones biometric features has not been widely implemented in a real time embedded system. Thus, in this paper, a novel approach to personal verification using infrared finger vein biometric authentication implemented on FPGA-based embedded system is presented. Creating a biometric authentication system in this resource-constrained embedded system for a real-time application, being a challenging problem in itself, is a significant contribution of this work. The proposed biometric system consists of four modules, namely image acquisition, image pre-processing, feature extraction, and matching. Feature extraction is based on minutiae extracted from the vein pattern image, while the biometric matching utilizes a technique based on the Modified Hausdorff Distance. The system is prototyped on Altera Stratix II FPGA hardware board with Nios2-Linux Real Time Operating System running at 100 MHz clock rate. Experiments conducted on a database of 100 images from 20 different hands shows encouraging results with system acceptable accuracy of less than 1.004%. Our first version of the embedded system, which is wholly in firmware, resulted in an execution time of 1953×10 6 clock cycles or 19 seconds. The results demonstrate that our approach is valid and effective for vein-pattern biometric authentication.
ISBN:1424476453
9781424476459
DOI:10.1109/ISIEA.2010.5679376