Hardware Implementation of Multimodal Biometric using Fingerprint and
Iris
- URL: http://arxiv.org/abs/2201.05996v1
- Date: Sun, 16 Jan 2022 07:59:14 GMT
- Title: Hardware Implementation of Multimodal Biometric using Fingerprint and
Iris
- Abstract summary: The proposed system is based on multiple biometric fusion that uses two biometric traits, fingerprint and iris.
To the best of the author's knowledge, no other FPGA-based design exits that used these two traits.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
Related papers
- Scalable Secure Biometric Authentication without Auxiliary Identifiers [54.032594016239926]
We present a new biometric authentication system that provides provable security guarantees against data breaches.<n>Our work is the first to show that real-world scalable privacy-preserving biometric authentication without auxiliary identifiers is feasible.
arXiv Detail & Related papers (2026-04-27T23:55:09Z) - Bi-Encoder Contrastive Learning for Fingerprint and Iris Biometrics [5.4450020653886355]
We train networks on three verification tasks, including fingerprint-to-fingerprint matching, iris-to-iris matching, and cross-modal fingerprint-to-iris matching.<n>We find that iris ResNet architecture reaches 91 ROC AUC score for iris-to-iris matching, providing clear evidence that the left and right irises of an individual are correlated.
arXiv Detail & Related papers (2025-10-27T02:41:43Z) - Multibiometrics Using a Single Face Image [0.11184789007828977]
We propose a novel multibiometric method that combines five biometric traits, i.e., face, iris, periocular, nose, eyebrow, that can be extracted from a single face image.
The proposed method does not sacrifice the convenience of biometrics since only a single face image is used as input.
arXiv Detail & Related papers (2024-09-30T06:55:01Z) - Multimodal Security of Iris and Fingerprint with Bloom Filters [0.0]
This paper will tell about basic concepts of iris, fingerprint, and securing iris with Cancellable Biometrics.
Here we are proposing a system for protecting iris templates using bloom filters with feature fusion of iris with fingerprint to provide security.
arXiv Detail & Related papers (2024-06-17T08:54:22Z) - FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance
and Altitude [67.55994773068191]
This paper presents the end-to-end design, development and evaluation of FarSight.
FarSight is an innovative software system designed for whole-body (fusion of face, gait and body shape) biometric recognition.
We test FarSight's effectiveness using the newly acquired IARPA Biometric Recognition and Identification at Altitude and Range dataset.
arXiv Detail & Related papers (2023-06-29T16:14:27Z) - Combining multiple matchers for fingerprint verification: A case study
in biosecure network of excellence [53.598636960435286]
Two reference systems for fingerprint verification have been tested together with two additional non-reference systems.
The experimental results show that the best recognition strategy involves both minutiae-based and correlation-based measurements.
arXiv Detail & Related papers (2022-12-04T19:49:05Z) - Facial Soft Biometrics for Recognition in the Wild: Recent Works,
Annotation, and COTS Evaluation [63.05890836038913]
We study the role of soft biometrics to enhance person recognition systems in unconstrained scenarios.
We consider two assumptions: 1) manual estimation of soft biometrics and 2) automatic estimation from two commercial off-the-shelf systems.
Experiments are carried out fusing soft biometrics with two state-of-the-art face recognition systems based on deep learning.
arXiv Detail & Related papers (2022-10-24T11:29:57Z) - Super-Resolution for Selfie Biometrics: Introduction and Application to
Face and Iris [67.74999528342273]
Lack of resolution has a negative impact on the performance of image-based biometrics.
Super-resolution techniques have to be adapted for the particularities of images from a specific biometric modality.
This chapter presents an overview of recent advances in super-resolution reconstruction of face and iris images.
arXiv Detail & Related papers (2022-04-12T10:28:31Z) - Mobile Behavioral Biometrics for Passive Authentication [65.94403066225384]
This work carries out a comparative analysis of unimodal and multimodal behavioral biometric traits.
Experiments are performed over HuMIdb, one of the largest and most comprehensive freely available mobile user interaction databases.
In our experiments, the most discriminative background sensor is the magnetometer, whereas among touch tasks the best results are achieved with keystroke.
arXiv Detail & Related papers (2022-03-14T17:05:59Z) - Synthesis and Reconstruction of Fingerprints using Generative
Adversarial Networks [6.700873164609009]
We propose a novel fingerprint synthesis and reconstruction framework based on the StyleGan2 architecture.
We also derive a computational approach to modify the attributes of the generated fingerprint while preserving their identity.
The proposed framework was experimentally shown to outperform contemporary state-of-the-art approaches for both fingerprint synthesis and reconstruction.
arXiv Detail & Related papers (2022-01-17T00:18:00Z) - Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal
Biometric Fusion Algorithms [58.156733807470395]
This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign.
The campaign targeted the application of physical access control in a medium-size establishment with some 500 persons.
To the best of our knowledge, this is the first attempt to benchmark quality-based multimodal fusion algorithms.
arXiv Detail & Related papers (2021-11-17T13:39:48Z) - Deep Hashing for Secure Multimodal Biometrics [1.7188280334580195]
We present a framework for feature-level fusion that generates a secure multimodal template from each user's face and iris biometrics.
We employ a hybrid secure architecture by combining cancelable biometrics with secure sketch techniques.
The proposed approach also provides cancelability and unlinkability of the templates along with improved privacy of the biometric data.
arXiv Detail & Related papers (2020-12-29T14:15:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.