Results 21 to 30 of about 351 (234)

On Multiview Analysis for Fingerprint Liveness Detection [PDF]

open access: yes, 2015
Fingerprint recognition systems, as any other biometric system, can be subject to attacks, which are usually carried out using artificial fingerprints. Several approaches to discriminate between live and fake fingerprint images have been presented to address this issue.
TOOSI, AMIRHOSEIN   +2 more
openaire   +1 more source

Fingerprint liveness detection through fusion of pores perspiration and texture features

open access: yesJournal of King Saud University: Computer and Information Sciences, 2022
Spoofing attacks on the fingerprint scanners become major and serious concern with the growing development and use of biometric technologies. Level 1 and Level 2 features; which are said to be unique and most commonly used features in fingerprint ...
Diwakar Agarwal, Atul Bansal
doaj   +1 more source

Fingerprint Liveness Detection Using Deep Learning

open access: yes2022 9th International Conference on Future Internet of Things and Cloud (FiCloud), 2022
It has great importance to provide the highest accuracy from fingerprint identification and verification systems, which have a large number of biometric features. Fingerprint recognition systems are more widely utilized than other biometric feature recognition systems.
Zeynep Inel Özkiper   +3 more
openaire   +2 more sources

Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid

open access: yesJournal of Electrical and Computer Engineering, 2018
Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for ...
Yujia Jiang, Xin Liu
doaj   +1 more source

RF Sensor-Based Liveness Detection Scheme With Loop Stability Compensation Circuit for a Capacitive Fingerprint System

open access: yesIEEE Access, 2019
A capacitive fingerprint system is the most widely used biometric identification method for smartphones. In this paper, we propose a RF sensor-based liveness detection scheme.
Woojung Kim   +4 more
doaj   +1 more source

A New Multi-Filter Framework for Texture Image Representation Improvement Using Set of Pattern Descriptors to Fingerprint Liveness Detection

open access: yesIEEE Access, 2022
The use of user recognition and authentication systems has become very common and is part of everyday routines for many people, guaranteeing access to the automatic teller machines, entrance to the gym or even to smartphones.
Rodrigo Colnago Contreras   +6 more
doaj   +1 more source

Fingerprint Liveness Detection Based on Fine-Grained Feature Fusion for Intelligent Devices

open access: yesMathematics, 2020
Currently, intelligent devices with fingerprint identification are widely deployed in our daily life. However, they are vulnerable to attack by fake fingerprints made of special materials.
Xinting Li   +5 more
doaj   +1 more source

LivDet2023 - Fingerprint Liveness Detection Competition: Advancing Generalization

open access: yes2023 IEEE International Joint Conference on Biometrics (IJCB), 2023
9 pages, 10 tables, IEEE International Joint Conference on Biometrics (IJCB 2023)
Micheletto, Marco   +7 more
openaire   +3 more sources

ENHANCED BORDER AUTHENTICATION USING MULTIMODAL BIOMETRICS [PDF]

open access: yesInternational Journal of Intelligent Computing and Information Sciences
The growing popularity of travel in the modern world coupled with inadequate authentication methods at border locations, has contributed to the rise of border security incidents.
Salma Abdelmonem   +7 more
doaj   +1 more source

Fingerprint liveness detection based on quality measures

open access: yes2009 First IEEE International Conference on Biometrics, Identity and Security (BIdS), 2009
A new fingerprint parameterization for liveness detection based on quality measures is presented. The novel feature set is used in a complete liveness detection system and tested on the development set of the LivDET competition, comprising over 4,500 real and fake images acquired with three different optical sensors.
Galbally, J.   +3 more
openaire   +4 more sources

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