192 research outputs found
Biometric antispoofing methods: A survey in face recognition
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. Galbally, S. Marcel and J. Fierrez, "Biometric Antispoofing Methods", IEEE Access, vol.2, pp. 1530-1552, Dec. 2014In recent decades, we have witnessed the evolution of biometric technology from the rst
pioneering works in face and voice recognition to the current state of development wherein a wide spectrum
of highly accurate systems may be found, ranging from largely deployed modalities, such as ngerprint,
face, or iris, to more marginal ones, such as signature or hand. This path of technological evolution has
naturally led to a critical issue that has only started to be addressed recently: the resistance of this rapidly
emerging technology to external attacks and, in particular, to spoo ng. Spoo ng, referred to by the term
presentation attack in current standards, is a purely biometric vulnerability that is not shared with other
IT security solutions. It refers to the ability to fool a biometric system into recognizing an illegitimate user
as a genuine one by means of presenting a synthetic forged version of the original biometric trait to the sensor.
The entire biometric community, including researchers, developers, standardizing bodies, and vendors, has
thrown itself into the challenging task of proposing and developing ef cient protection methods against this
threat. The goal of this paper is to provide a comprehensive overview on the work that has been carried out
over the last decade in the emerging eld of antispoo ng, with special attention to the mature and largely
deployed face modality. The work covers theories, methodologies, state-of-the-art techniques, and evaluation
databases and also aims at providing an outlook into the future of this very active eld of research.This work was supported in part by the CAM under Project S2009/TIC-1485, in part by the Ministry of Economy and Competitiveness through the Bio-Shield Project under Grant TEC2012-34881, in part by the TABULA RASA Project under Grant FP7-ICT-257289, in part by the BEAT Project under Grant FP7-SEC-284989 through the European Union, and in part by the Cátedra Universidad Autónoma de Madrid-Telefónica
Evaluating the Sensitivity of Face Presentation Attack Detection Techniques to Images of Varying Resolutions
In the last decades, emerging techniques for face Presentation Attack Detection (PAD) have reported a remarkable performance to detect attack presentations whose attack type and capture conditions are known a priori. However, the generalisation capability of PAD approaches shows a considerable deterioration to detect unknown attacks. In order to tackle those generalisation issues, several PAD techniques have focused on the detection of homogeneous features from known attacks to detect unknown Presentation Attack Instruments without taking into account how some intrinsic image properties such as the image resolution or biometric quality could impact their detection performance. In this work, we carry out a thorough analysis of the sensitivity of several texture descriptors which shows how the use of images with varying resolutions for training leads to a high decrease on the attack detection performance
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