CRCVJan 16, 2022

Hardware Implementation of Multimodal Biometric using Fingerprint and Iris

arXiv:2201.05996v14 citations
Originality Synthesis-oriented
AI Analysis

This work provides a domain-specific solution for biometric security by combining fingerprint and iris recognition in hardware, but it is incremental as it builds on existing biometric methods.

The paper presents a hardware architecture for a multimodal biometric system using fingerprint and iris, optimizing software to address false acceptance and rejection rates and implementing it on FPGA for parallelism.

In this paper, a hardware architecture of a multimodal biometric system is presented that massively exploits the inherent parallelism. The proposed system is based on multiple biometric fusion that uses two biometric traits, fingerprint and iris. Each biometric trait is first optimised at the software level, by addressing some of the issues that directly affect the FAR and FRR. Then the hardware architectures for both biometric traits are presented, followed by a final multimodal hardware architecture. To the best of the author's knowledge, no other FPGA-based design exits that used these two traits.

Foundations

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