Deep convolutional neural network for double-identity fingerprint detection

I Goel, NB Puhan, B Mandal - IEEE Sensors Letters, 2020 - ieeexplore.ieee.org
Automatic human recognition using ubiquitous fingerprint sensors is the most widely used
modality in modern biometric based security systems. The double-identity fingerprint is a …

On the feasibility of creating double-identity fingerprints

M Ferrara, R Cappelli, D Maltoni - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
A double-identity fingerprint is a fake fingerprint created by combining features from two
different fingers, so that it has a high chance to be falsely matched with fingerprints from both …

Patch-based fake fingerprint detection using a fully convolutional neural network with a small number of parameters and an optimal threshold

E Park, X Cui, W Kim, J Liu, H Kim - arXiv preprint arXiv:1803.07817, 2018 - arxiv.org
Fingerprint authentication is widely used in biometrics due to its simple process, but it is
vulnerable to fake fingerprints. This study proposes a patch-based fake fingerprint detection …

2D fake fingerprint detection based on improved CNN and local descriptors for smart phone

Y Zhang, B Zhou, H Wu, C Wen - … 2016, Chengdu, China, October 14-16 …, 2016 - Springer
With the growing use of fingerprint authentication systems on smart phone, fake fingerprint
detection has become increasingly important because fingerprints can be easily spoofed …

A comprehensive survey of fingerprint presentation attack detection

K Karampidis, M Rousouliotis, E Linardos… - 2021 - repository-empedu-rd.ekt.gr
Nowadays, the number of people that utilize either digital applications or machines is
increasing exponentially. Therefore, trustworthy verification schemes are required to ensure …

Fingerprint generation and presentation attack detection using deep neural networks

H Kim, X Cui, MG Kim… - 2019 IEEE Conference on …, 2019 - ieeexplore.ieee.org
Performance evaluation of fingerprint recognition systems requires large-scale databases.
Unfortunately, collecting fingerprints is expensive and time-consuming, and publishing them …

Single architecture and multiple task deep neural network for altered fingerprint analysis

O Giudice, M Litrico, S Battiato - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Fingerprints are one of the most copious evidence in a crime scene and, for this reason, they
are frequently used by law enforcement for identification of individuals. But fingerprints can …

Fingerprint template invertibility: Minutiae vs. deep templates

KP Wijewardena, SA Grosz, K Cao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Much of the success of fingerprint recognition is attributed to minutiae-based fingerprint
representation. It was believed that minutiae templates could not be inverted to obtain a high …

Lightweight convolutional neural network based on singularity ROI for fingerprint classification

W Jian, Y Zhou, H Liu - IEEE Access, 2020 - ieeexplore.ieee.org
Fingerprint classification is a significant guarantee for efficient and accurate fingerprint
recognition, especially when dealing with one-to-many fingerprint recognition. However, due …

Fingerprint spoof detection using contrast enhancement and convolutional neural networks

HU Jang, HY Choi, D Kim, J Son, HK Lee - Information Science and …, 2017 - Springer
Recently, as biometric technology grows rapidly, the importance of fingerprint spoof
detection technique is emerging. In this paper, we propose a technique to detect forged …