38 research outputs found
Convolutional neural network-based finger vein recognition using near infrared images
Convolutional Neural Network (CNN) is opening
new horizons in biometrics-based authentication field and
finger vein recognition is the prominent one which can provide
the best possible security system depending on this
aforementioned technology. In this paper, we used 5
convolutional layers and 4 fully-connected layers where our
developed network has shown the capability to produce the
result with almost 100% accuracy rate which became possible
due to the fact that deep learning, an end-to-end system is used
which performs better in a lot of aspects in comparison to
conventional techniques.Convolutional Neural Network (CNN) is opening
new horizons in biometrics-based authentication field and
finger vein recognition is the prominent one which can provide
the best possible security system depending on this
aforementioned technology. In this paper, we used 5
convolutional layers and 4 fully-connected layers where our
developed network has shown the capability to produce the
result with almost 100% accuracy rate which became possible
due to the fact that deep learning, an end-to-end system is used
which performs better in a lot of aspects in comparison to
conventional techniques
Biometric presentation attack detection: beyond the visible spectrum
The increased need for unattended authentication in
multiple scenarios has motivated a wide deployment of biometric
systems in the last few years. This has in turn led to the
disclosure of security concerns specifically related to biometric
systems. Among them, presentation attacks (PAs, i.e., attempts
to log into the system with a fake biometric characteristic or
presentation attack instrument) pose a severe threat to the
security of the system: any person could eventually fabricate
or order a gummy finger or face mask to impersonate someone
else. In this context, we present a novel fingerprint presentation
attack detection (PAD) scheme based on i) a new capture device
able to acquire images within the short wave infrared (SWIR)
spectrum, and i i) an in-depth analysis of several state-of-theart
techniques based on both handcrafted and deep learning
features. The approach is evaluated on a database comprising
over 4700 samples, stemming from 562 different subjects and
35 different presentation attack instrument (PAI) species. The
results show the soundness of the proposed approach with a
detection equal error rate (D-EER) as low as 1.35% even in a
realistic scenario where five different PAI species are considered
only for testing purposes (i.e., unknown attacks
On the Generalisation Capabilities of Fingerprint Presentation Attack Detection Methods in the Short Wave Infrared Domain
Nowadays, fingerprint-based biometric recognition systems are becoming
increasingly popular. However, in spite of their numerous advantages, biometric
capture devices are usually exposed to the public and thus vulnerable to
presentation attacks (PAs). Therefore, presentation attack detection (PAD)
methods are of utmost importance in order to distinguish between bona fide and
attack presentations. Due to the nearly unlimited possibilities to create new
presentation attack instruments (PAIs), unknown attacks are a threat to
existing PAD algorithms. This fact motivates research on generalisation
capabilities in order to find PAD methods that are resilient to new attacks. In
this context, we evaluate the generalisability of multiple PAD algorithms on a
dataset of 19,711 bona fide and 4,339 PA samples, including 45 different PAI
species. The PAD data is captured in the short wave infrared domain and the
results discuss the advantages and drawbacks of this PAD technique regarding
unknown attacks
Liveness Detection on Fingers Using Vein Pattern
Tato práce se zabývá rozšířením snímače otisků prstů Touchless Biometric Systems 3D-Enroll o jednotku detekce živosti prstu na základě žil. Bylo navrhnuto a zkonstruováno hardwarové řešení s využitím infračervených diod. Navržené softwarové řešení pracuje ve dvou různých režimech: detekce živosti na základě texturních příznaků a verifikace uživatelů na základě porovnávání žilních vzorů. Datový soubor obsahující přes 1100 snímků jak živých prstů tak jejich falsifikátů vznikl jako součást této práce a výkonnost obou zmíněných režimů byla vyhodnocena na tomto datovém souboru. Na závěr byly navrhnuty materiály vhodné k výrobě falsifikátů otisků prstů umožňující oklamání detekce živosti pomocí žilních vzorů.This work presents liveness detection extension of the Touchless Biometric Systems 3D-Enroll fingerprint sensor which is based on finger vein pattern. Hardware solution was designed and realized using infrared diodes. Designed software system operates in two different modes: liveness detection based on texture features and user verification using finger vein matching. A dataset containing more than 1,100 images of both real fingers and their falsifications was gathered. Performance of both proposed modes was evaluated using mentioned dataset and suitable materials, that can fool the liveness detection module, were highlighted.
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