Study of Applicability of Virtual Users in Evaluating Multimodal Biometrics

Abstract. A new approach of enlarging fused biometric databases is presented. Fusion strategies based upon matching score are applied on active biometrics verification scenarios. Consistent biometric data of two traits are used in test scenarios of handwriting and speaker verification. The fusion strategies are applied on multimodal biometrics of two different user types. The real users represent two biometric traits captured from one person. The virtual users are considered as the combination of two traits captured from two discrete users. These virtual users are implemented for database enlargement. In order to investigate the impact of these virtual users, test scenarios using three different semantics of handwriting and speech are accomplished. The results of fused handwriting and speech of exclusively real users and additional virtual users are compared and discussed

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

Automatically verifying the identity of a person by means of biometrics is an important application in 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, 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 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 template and query data. The response to the call of the campaign proved very encouraging, with the submission of 22 fusion systems. To the best of our knowledge, this is the first attempt to benchmark quality-based multimodal fusion algorithms

Scheidat: Multimodal Biometrics for Voice and Handwriting

Abstract. In this paper a novel fusion approach for combining voice and online signature verification will be introduced. While the matching algorithm for the speaker identification modality is based on a single Gaussian Mixture Model (GMM) algorithm, the signature verification strategy is based on four different distance measurement functions, combined by multialgorithmic fusion. Together with a feature extraction method presented in our earlier work, the Biometric Hash algorithm, they result in four verification experts for the handwriting subsystem. The fusion results of our new subsystem on the multimodal level are elaborated by enhancements to a system, which was previously introduced by us for biometric authentication in HCI scenarios. Tests have been performed on identical data sets for the original and the enhanced system and the first results presented in this paper show that an increase of recognition accuracy can be achieved by our new multialgorithmic approach for the handwriting modality

Analyzing a multimodal biometric system using real and virtual users

Three main topics of recent research on multimodal biometric systems are addressed in this article: The lack of sufficiently large multimodal test data sets, the influence of cultural aspects and data protection issues of multimodal biometric data. In this contribution, different possibilities are presented to extend multimodal databases by generating so-called virtual users, which are created by combining single biometric modality data of different users. Comparative tests on databases containing real and virtual users based on a multimodal system using handwriting and speech are presented, to study to which degree the use of virtual multimodal databases allows conclusions with respect to recognition accuracy in comparison to real multimodal data. All tests have been carried out on databases created from donations from three different nationality groups. This allows to review the experimental results both in general and in context of cultural origin. The results show that in most cases the usage of virtual persons leads to lower accuracy than the usage of real users in terms of the measurement applied: the Equal Error Rate. Finally, this article will address the general question how the concept of virtual users may influence the data protection requirements for multimodal evaluation databases in the future

Short Term Template Aging Effects on Biometric Dynamic Handwriting Authentication Performance

Part 2: Work in ProgressInternational audienceIn biometrics the variance between data acquired from the same user and same trait is not only based on different sensors or user’s form of the day, but it also depends on an aging factor. Over time the biological characteristics of a human body changes. This leads to physical and mental alternations, which may have significant influence on the biometric authentication process. In order to parameterize a biometric system, the study of the degree of aging’s influence is an important step. In this paper we provide an experimental evaluation on the influence of changes of handwriting biometrics by acquiring data from writers in three sessions with a time difference of one month each. The aim is to analyze the potential impact of aging processes on different written content within a biometric handwriting system in terms of authentication performance. In the worst case, the equal error rate determined on verification data acquired two month after the reference data (EER = 0.162) is four times higher than the equal error rate calculated based on reference and verification data from the first session (EER = 0.041)

Distance-level fusion strategies for online signature verification

In this paper an approach for combining online signature authentication experts will be proposed. The different experts are based on one feature extraction method presented in our earlier work, the Biometric Hash algorithm [1], to which different distance measurement functions are applied. We will show that by the fusion of several algorithms with an appropriately parameterized strategy an improvement of the recognition accuracy can be achieved. The best fusion strategy results in a decrease of the EER of 12.1 % in comparison to the best individual algorithm. The database we used contains 1761 genuine enrollments (with 4 signatures per enrollment), 1101 genuine verification signatures and 431 well skilled forgeries (so-called “brute force attack”) by 22 persons. Based on our experimental results, we further discuss usability of alternative handwriting semantics such as pass phrases or PIN

Parameter optimization for biometric fingerprint recognition using genetic algorithms

In this paper, we suggest an optimization approach for fingerprint authentication using genetic algorithms. Our application was planned so that it can be used without great effort for different biometric systems. Instead of estimating the required parameters as in the case of some methods, here they are determined with the help of genetic algorithms. Our own test database consists of 1200 fingerprints of 12 persons. For the confirmation of the results, which were found out with this test set, the databases of the Fingerprint Verification Contests of the years 2000, 2002 and 2004 were examined in addition. In the best case an improvement in the recognition performance of 38 % could be observed. Categories and Subject Descriptors C.4 [Performance of Systems]: Measurement techniques, Performance attribute

From Biometrics to Forensics: A Feature Collection and First Feature Fusion Approaches for Latent Fingerprint Detection Using a Chromatic White Light (CWL) Sensor

Part 3: Extended AbstractsInternational audienceApplication of non-invasive scan technologies for acquisition of latent fingerprints promise a better support of forensic and dactyloscopic experts when securing evidence at crime scenes. Furthermore, non-destructive acquisition preserve the chance of subsequent chemical and forensic analysis of left residue. Based on results of an ongoing research project with sensor industry partners, this paper presents a collection of 28 statistical, gradient-, and spectral density-based features for latent fingerprint detection using low resolution scans. Within this work a chromatic white light (CWL) sensor is used for image acquisition. Furthermore, based on concepts of biometric fusion, a taxonomy for possible fusion strategies is presented and very first results for three different strategies on decision level are discussed. Experimental evaluation is performed based on scans of 1680 latent fingerprints on three different surfaces. The results show very good performance on planar, non-absorbing surfaces with uniform reflection characteristics with an detection rate of 2.51% in the best case. On the other hand difficulties are arising from surfaces with non-uniform/predictable reflection characteristics

MINT-Interessensförderung für junge Frauen ab Klasse 8

Ziel der intoMINT-App ist es, Mädchen ab Klasse 8 zum Auseinandersetzen mit Mathematik, Informatik, Naturwissenschaften und Technik (kurz MINT) über kurzweilige Aktivitäten und (digitale) Anreize anzuregen und dies mit einer gendersensiblen Berufs- und Studienorientierung zu verknüpfen. In diesem Artikel wird zunächst die in einem Förderprojekt entwickelte App beschrieben und gezeigt, wie die Motivation der Zielgruppe durch altersgerechte Aufbereitung von Inhalten und Einsatz von Elementen der Gamification sowie das Anbieten von Informationen zu relevanten Berufsbildern erreicht werden kann. Die App schlägt dabei die Brücke von der digitalen Welt in das reale Erleben durch eigenes Nachmachen zu Hause und wieder zurück durch die In-App-Dokumentation und -Reflektion des Gemachten und lädt zur Interaktion mit dem Projektteam ein. Darüber hinaus wird gezeigt, wie die Nutzung der App durch ein Begleitprogramm, z.B. in Form eines Wettbewerbsevents, angeregt werden kann.Aim of the intoMINT app is to encourage girls grade 8 or higher to engage with science, technology, engineering and mathematics (STEM for short) through entertaining activities and (digital) incentives. This is linked with a gender-sensitive career and study orientation. This article describes the app developed in a funded project and shows how motivation of the target group can be achieved through age and gender appropriate preparation of content and elements of gamification as well as through providing information on relevant job profiles. The app establishes ties between digital world and real-life experience: users “re-do” digitally described activities at home and document and reflect their real life experience through the app. Furthermore, it is shown how app usage can be stimulated by an accompanying program, e.g. in form of a competition event