Lorene Allano

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. 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. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms

Automatically verifying the identity of a person by means of biometrics (e.g., face and fingerprint) is an important application in our day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal biometric system. This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign organized by the University of Surrey, involving face, fingerprint, and iris biometrics for person authentication, targeting the application of physical access control in a medium-size establishment with some 500 persons. While multimodal biometrics is a well-investigated subject in the literature, there exists no benchmark for a fusion algorithm comparison. Working towards this goal, we designed two sets of experiments: quality-dependent and cost-sensitive evaluation. The quality-dependent evaluation aims at assessing how well fusion algorithms can perform under changing quality of raw biometric images principally due to change of devices. The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match. Since multiple capturing devices are available, a fusion algorithm should be able to handle this nonideal but nevertheless realistic scenario. In both evaluations, each fusion algorithm is provided with scores from each biometric comparison subsystem as well as the quality measures of both the template and the query data. The response to the call of the evaluation campaign proved very encouraging, with the submission of 22 fusion systems. To the best of our knowledge, this campaign is the first attempt to benchmark quality-based multimodal fusion algorithms. In the presence of changing image quality which may be due to a change of acquisition devices and/or device capturing configurations, we observe that the top performing fusion algorithms are those that exploit automatically derived quality measurements. Our evaluation also suggests that while using all the available biometric sensors can definitely increase the fusion performance, this comes at the expense of increased cost in terms of acquisition time, computation time, the physical cost of hardware, and its maintenance cost. As demonstrated in our experiments, a promising solution which minimizes the composite cost is sequential fusion, where a fusion algorithm sequentially uses match scores until a desired confidence is reached, or until all the match scores are exhausted, before outputting the final combined score.

Biosecure reference systems for on-line signature verification: a study of complementarity

In this paper, we present an integrated research study in On-line Signature Verification undertaken by several teams that participate in the BioSecure Network of Excellence. This integrated work started during the First BioSecure Residential Workshop, has as main objective the development of an On-line Signature Verification evaluation platform. As a first step, four On-line Signature Verification Systems based on different approaches are evaluated and compared following the same experimental protocol on MCYT signature database, which is the largest existing on-line western signature database publicly available with 16500 signatures from 330 clients. A particular focus of work documented in this paper is multi-algorithmic fusion in order to study the complementarity of the approaches involved. To this end, a simple fusion method based on the Mean Rule is used after a normalization phase.RésuméDans cet article, nous présentons un travail commun sur la vérification de signature enligne, réalisé par 4 équipes qui participent au Réseau d’Excellence BioSecure. Ce travail commun, débuté durant le premier « Workshop » résidentiel, a pour principal objectif le développement d’une plateforme d’évaluation pour la vérification de la signature en-ligne. Tout d’abord, quatre systèmes de vérification de signature en-ligne basés sur différentes approaches sont évalués et comparés en utilisant le même protocole expérimental sur la base de signatures MCYT, la plus grande base existante de signatures en-ligne disponible, avec 16500 signatures de 330 personnes. Ensuite, l’accent est mis sur la fusion multi-algorithmique afin d’étudier la complémentarité des approches impliquées. Pour cela, une méthode de fusion simple est utilisée, basée sur une moyenne des scores après une phase de normalisation.

Nonintrusive multibiometrics on a mobile device: a comparison of fusion techniques

In this article we test a number of score fusion methods for the purpose of multimodal biometric authentication. These tests were made for the SecurePhone project, whose aim is to develop a prototype mobile communication system enabling biometrically authenticated users to deal legally binding m-contracts during a mobile phone call on a PDA. The three biometrics of voice, face and signature were selected because they are all traditional non-intrusive and easy to use means of authentication which can readily be captured on a PDA. By combining multiple biometrics of relatively low security it may be possible to obtain a combined level of security which is at least as high as that provided by a PIN or handwritten signature, traditionally used for user authentication. As the relative success of different fusion methods depends on the database used and tests made, the database we used was recorded on a suitable PDA (the Qtek2020) and the test protocol was designed to reflect the intended application scenario, which is expected to use short text prompts. Not all of the fusion methods tested are original. They were selected for their suitability for implementation within the constraints imposed by the application. All of the methods tested are based on fusion of the match scores output by each modality. Though computationally simple, the methods tested have shown very promising results. All of the 4 fusion methods tested obtain a significant performance increase.

Specific texture analysis for iris recognition

In this paper, we present a new method for iris recognition based on specific texture analysis. It relies on the use of Haar wavelet analysis to extract the texture of the iris tissue. The matching is done using a specific correlation based on local peaks detection. Experiments have been conducted on the CASIA database in verification mode and show an EER of 0.07%. Degraded version of the CASIA database results in an EER of 2.3%, which is lower than result obtained by the classical wavelet demodulation (WD) method in that database.

Multimodality In Biosecure: Evaluation On Real Vs. Virtual Subjects

In this paper, we present the BioSecure Network of Excellence and its objectives in terms of biometric evaluation. A particular focus is given in this project to multimodal evaluation, which requires special attention due to the lack of large-size available multimodal databases. We show in this paper that the evaluation of score fusion methods for two a priori independent modalities is possible on standard size (roughly 100 persons) virtual databases, but at the price of a careful statistical protocol

A generic protocol for multibiometric systems evaluation on virtual and real subjects

We propose in this paper a methodology for multibiometric systems evaluation on databases of virtual and real subjects of limited size (about 100 persons). Our study is limited to two biometric traits (modalities) that are a priori mutually independent, namely on-line signature and voice. Experiments are conducted on bimodal data of real subjects of the BIOMET database [9] and on several databases of virtual subjects constructed from BIOMET.

BioSecure Multimodal Evaluation Campaign 2007 (BMEC’2007)

This chapter presents the experimental results from the mobile scenario of the BioSecure Multimodal Evaluation Campaign 2007 (BMEC’2007). This competition was organized by the BioSecure Network of Excellence (NoE) and aimed at testing the robustness of monomodal and multimodal biometric verification systems to degraded acquisition conditions. The database used for the evaluation is the large-scale multimodal database acquired in the framework of the BioSecure NoE in mobility conditions. During this evaluation, the BioSecure benchmarking methodology was followed to enable a fair comparison of the submitted algorithms. In this way, we believe that the BMEC’2007 database and results will be useful both to the participants and, more generally, to all practitioners in the field as a benchmark for improving methods and for enabling evaluation of algorithms.

An adaptive multi-biometric incremental fusion strategy in the context of BMEC 2007

We present the general principles of a dynamical sequential fusion strategy for multibiometric systems allowing reducing the cost associated to the use of different modalities while preserving a good performance compared to that of a global fusion system. We have implemented this strategy in the BMEC (BioSecure multimodal evaluation campaign) 2007 cost-sensitive evaluation. We show that this approach was very robust to the occurrence of missing data thanks to its adaptive implementation.