no code implementations • 5 Jan 2024 • Marta Gomez-Barrero, Javier Galbally
With the widespread use of biometric recognition, several issues related to the privacy and security provided by this technology have been recently raised and analysed.
no code implementations • 8 Nov 2023 • Marta Gomez-Barrero, Javier Galbally, Christian Rathgeb, Christoph Busch
The wide deployment of biometric recognition systems in the last two decades has raised privacy concerns regarding the storage and use of biometric data.
no code implementations • 11 Jul 2022 • Javier Galbally, Fernando Alonso-Fernandez, Julian Fierrez, Javier Ortega-Garcia
A new fingerprint parameterization for liveness detection based on quality measures is presented.
no code implementations • 11 Jul 2022 • Javier Galbally, Julian Fierrez-Aguilar, Joaquin Rodriguez-Gonzalez, Fernando Alonso-Fernandez, Javier Ortega-Garcia, Marino Tapiador
A new method to generate gummy fingers is presented.
no code implementations • 24 Nov 2021 • Aythami Morales, Julian Fierrez, Javier Galbally, Marta Gomez-Barrero
Iris recognition technology has attracted an increasing interest in the last decades in which we have witnessed a migration from research laboratories to real world applications.
no code implementations • 23 Nov 2021 • Javier Hernandez-Ortega, Julian Fierrez, Aythami Morales, Javier Galbally
The main scope of this chapter is to serve as an introduction to face presentation attack detection, including key resources and advances in the field in the last few years.
no code implementations • 17 Nov 2021 • Javier Ortega-Garcia, Julian Fierrez, Fernando Alonso-Fernandez, Javier Galbally, Manuel R Freire, Joaquin Gonzalez-Rodriguez, Carmen Garcia-Mateo, Jose-Luis Alba-Castro, Elisardo Gonzalez-Agulla, Enrique Otero-Muras, Sonia Garcia-Salicetti, Lorene Allano, Bao Ly-Van, Bernadette Dorizzi, Josef Kittler, Thirimachos Bourlai, Norman Poh, Farzin Deravi, Ming NR Ng, Michael Fairhurst, Jean Hennebert, Andreas Humm, Massimo Tistarelli, Linda Brodo, Jonas Richiardi, Andrezj Drygajlo, Harald Ganster, Federico M Sukno, Sri-Kaushik Pavani, Alejandro Frangi, Lale Akarun, Arman Savran
It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware.
no code implementations • 2 Nov 2021 • Julian Fierrez, Javier Galbally, Javier Ortega-Garcia, Manuel R Freire, Fernando Alonso-Fernandez, Daniel Ramos, Doroteo Torre Toledano, Joaquin Gonzalez-Rodriguez, Juan A Siguenza, Javier Garrido-Salas, E Anguiano, Guillermo Gonzalez-de-Rivera, Ricardo Ribalda, Marcos Faundez-Zanuy, JA Ortega, Valentín Cardeñoso-Payo, A Viloria, Carlos E Vivaracho, Q Isaac Moro, Juan J Igarza, J Sanchez, Inmaculada Hernaez, Carlos Orrite-Urunuela, Francisco Martinez-Contreras, Juan José Gracia-Roche
A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol.
no code implementations • 2 Nov 2021 • Javier Galbally, Fernando Alonso-Fernandez, Julian Fierrez, Javier Ortega-Garcia
A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed.
no code implementations • 30 Oct 2021 • Virginia Ruiz-Albacete, Pedro Tome-Gonzalez, Fernando Alonso-Fernandez, Javier Galbally, Julian Fierrez, Javier Ortega-Garcia
In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied.
1 code implementation • 13 Aug 2021 • Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia, Julian Fierrez, Aythami Morales, Javier Ortega-Garcia, Juan Carlos Ruiz-Garcia, Sergio Romero-Tapiador, Santiago Rengifo, Miguel Caruana, Jiajia Jiang, Songxuan Lai, Lianwen Jin, Yecheng Zhu, Javier Galbally, Moises Diaz, Miguel Angel Ferrer, Marta Gomez-Barrero, Ilya Hodashinsky, Konstantin Sarin, Artem Slezkin, Marina Bardamova, Mikhail Svetlakov, Mohammad Saleem, Cintia Lia Szucs, Bence Kovari, Falk Pulsmeyer, Mohamad Wehbi, Dario Zanca, Sumaiya Ahmad, Sarthak Mishra, Suraiya Jabin
This article presents SVC-onGoing, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-scale public databases, such as DeepSignDB and SVC2021_EvalDB, and standard experimental protocols.
1 code implementation • 1 Jun 2021 • Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia, Julian Fierrez, Santiago Rengifo, Aythami Morales, Javier Ortega-Garcia, Juan Carlos Ruiz-Garcia, Sergio Romero-Tapiador, Jiajia Jiang, Songxuan Lai, Lianwen Jin, Yecheng Zhu, Javier Galbally, Moises Diaz, Miguel Angel Ferrer, Marta Gomez-Barrero, Ilya Hodashinsky, Konstantin Sarin, Artem Slezkin, Marina Bardamova, Mikhail Svetlakov, Mohammad Saleem, Cintia Lia Szücs, Bence Kovari, Falk Pulsmeyer, Mohamad Wehbi, Dario Zanca, Sumaiya Ahmad, Sarthak Mishra, Suraiya Jabin
This paper describes the experimental framework and results of the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021).
no code implementations • 2 Sep 2020 • Torsten Schlett, Christian Rathgeb, Olaf Henniger, Javier Galbally, Julian Fierrez, Christoph Busch
The performance of face analysis and recognition systems depends on the quality of the acquired face data, which is influenced by numerous factors.
2 code implementations • 5 Jun 2020 • Javier Hernandez-Ortega, Javier Galbally, Julian Fierrez, Laurent Beslay
After a gentle introduction to the general topic of biometric quality and a review of past efforts in face quality metrics, in the present work, we address the need for better face quality metrics by developing FaceQnet.
7 code implementations • 3 Apr 2019 • Javier Hernandez-Ortega, Javier Galbally, Julian Fierrez, Rudolf Haraksim, Laurent Beslay
Several conclusions can be drawn from this work, most notably: 1) we managed to employ an existing ICAO compliance framework and a pretrained CNN to automatically label data with quality information, 2) we trained FaceQnet for quality estimation by fine-tuning a pre-trained face recognition network (ResNet-50), and 3) we have shown that the predictions from FaceQnet are highly correlated with the face recognition accuracy of a state-of-the-art commercial system not used during development.