P212 - BIOSIG 2013 - Proceedings of the 12th International Conference of the Biometrics Special Interest Group
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- KonferenzbeitragAssignment of the evidential value of a fingermark general pattern using a Bayesian network(BIOSIG 2013, 2013) Haraksim, Rudolf; Meuwly, Didier; Doekhie, Gina; Vergeer, Peter; Sjerps, MarjanWhen visible on a fingermark, the general pattern maintains its importance in the fingerprint examination procedure, since the difference between the general pattern of a fingermark and a fingerprint is sufficient for exclusion. In the current work, the importance of the general pattern is extended by evaluating the strength of evidence of a match given corresponding general pattern. In current practice (due to the lack of statistical support for the general pattern evidence) the fingerprint examiners assign personal probabilities to the general pattern evidence based on their knowledge and experience, while in this work the probabilities are calculated using a Bayesian Network which is fed by empirical data.
- KonferenzbeitragSocial acceptance of biometric technologies in Germany: A survey(BIOSIG 2013, 2013) Krupp, Alina; Rathgeb, Christian; Busch, ChristophSince the past decade biometric technologies are field-proven, facilitating reliable and secure access control. Numerous successful deployments on large-scale systems, e.g. airports, confirm the feasibility of biometric recognition. However, applications of biometric systems involve privacy concerns, i.e. debates on social and ethical acceptance of biometrics reached levels never previously witnessed. In this work a comprehensive questionnaire regarding social acceptance of biometric technologies in Germany is presented. Results are obtained from a total number of 140 respondents, allowing a representative analysis of citizens' attitudes towards biometric technologies. Relevant questions are put into view and perceptions of German citizens regarding the rise of biometric technologies are discussed in detail and interesting conclusions are drawn.
- KonferenzbeitragSpoofing 2D face recognition systems with 3D masks(BIOSIG 2013, 2013) Erdogmus, Nesli; Marcel, SébastienVulnerability to spoofing attacks is a serious drawback for many biometric systems. Among all biometric traits, face is the one that is exposed to the most serious threat, since it is exceptionally easy to access. The limited work on fraud detection capabilities for face mainly shapes around 2D attacks forged by displaying printed photos or replaying recorded videos on mobile devices. A significant portion of this work is based on the flatness of the facial surface in front of the sensor. In this study, we complicate the spoofing problem further by introducing the 3rd dimension and examine possible 3D attack instruments. A small database is constructed with six different types of 3D facial masks and experimented on to determine the right direction to study 3D attacks. Spoofing performance for each type of mask is assessed and analysed thoroughly using two Gabor-wavelet-based algorithms.
- KonferenzbeitragAn efficient 3D facial landmark detection algorithm with Haar-like features and anthropometric constraints(BIOSIG 2013, 2013) Böckeler, Martin; Zhou, XuebingIn the last few years 3D face recognition has become more and more popular due to reducing cost of scanners and increasing computational power. The crucial and time-consuming step is landmark localization and normalization of facial surface. Due to acquisition, noise and other artifacts like spikes and holes occur. Most systems require computational intensive preprocessing steps to eliminate these artifacts. As a consequence, a trade-off between runtime or detection accuracy must be made. In contrast, we propose a landmark detection algorithm which uses the Viola & Jones classifier on gradient images. The algorithm is able to reliably detect landmarks in raw 3D data without complicated preprocessing. Additionally, selection of sub regions is exploited to limit search regions. It further reduces false detection rate and improves significantly detection accuracy.
- KonferenzbeitragBioHashing with fingerprint spectral minutiae(BIOSIG 2013, 2013) Topcu, Berkay; Erdogan, Hakan; Karabat, Cagatay; Yanikoglu, BerrinIn recent years, the interest in human authentication has been increasing. Biometrics are one of the easy authentication schemes, however, security and privacy problems limit their widespread usage. Following the interest in privacy protecting biometric authentication, template protection schemes for biometric modalities has increased significantly in order to cope with security and privacy issues. BioHashing, which is based on transforming the biometric template using pseudo-random projections that are generated using a user-specified key or token, has received much attention as it improves verification accuracies over using only the biometric data, allows template revocation and preserves privacy. In our work, we develop a new BioHashing scheme for fingerprints. A fixed-length feature vector is required in order to design a BioHashing scheme. In the literature, most of the studies on fingerprint BioHashing uses features extracted from fingerprint texture. On the other hand, our new BioHashing scheme is based on minutia based feature vectors. We use the spectral minutiae representation for obtaining a fixed-length feature vector for a fingerprint sample. Then, we use a random projection matrix, which is generated from user's key/token, in order to generate a BioHash vector. We propose to randomly project each column of the spectral minutiae feature matrix via a single matrix which allows fast bit string extraction and adaptive quantization. Experiments on FVC2002 databases show the promise of the proposed system for fast and secure verification.
- KonferenzbeitragSolving terminal revocationin EAC by augmenting terminal authentication(BIOSIG 2013, 2013) Chaabouni, RafikIn this paper we propose a solution to enable an accurate terminal revocation in the Extended Access Control (EAC). Chaabouni and Vaudenay in [CV09] pointed out the need for an accurate revocation procedure, but failed to provide a complete solution description. We aim at filling this gap. Our solution relies on augmenting terminal authentication with a t-out-ofthreshold signature provided by neighboring terminals. These terminals will be in charge of checking the revocation status of the requested terminal. As Terminals have a real clock embedded and more computational power than Machine Readable Travel Documents (MRTDs), they are better suited for checking revocation status.
- KonferenzbeitragA template privacy protection scheme for fingerprint minutiae descriptors(BIOSIG 2013, 2013) Mirmohamadsadeghi, Leila; Drygajlo, AndrzejIt is important in biometric person recognition systems to protect personal data and privacy of users. This paper introduces a new mechanism to revoke and protect fingerprint minutiae information, which can be used in today's security-aware society. The recently developed minutiae cylinder code (MCC), which provides rotation and translation invariant descriptors for accurate fingerprint recognition by describing minutiae neighborhoods with respect to each other, is used as baseline fingerprint descriptor. A hybrid scheme combining a transformation and a user key is designed to provide the MCC-based fingerprint representation with revocability and irreversibility properties for template privacy protection across multiple applications. Furthermore, using the publicly available FVC datasets, it is demonstrated that the designed scheme improves the baseline accuracy of fingerprint recognition using the MCC method.
- Editiertes BuchBIOSIG 2013(2013)
- KonferenzbeitragQuality filtering of EEG signals for enhanced biometric recognition(BIOSIG 2013, 2013) Yang, Su; Deravi, FarzinIn this paper we present a biometric person recognition system based on EEG signals incorporating a novel strategy to find and utilize the most informative data segments using the concept of Sample Entropy. The users are presented with a stimulus that prompts a motor-imagery response. This is then measured using an array of EEG sensors. A sliding-window segmentation scheme and Wavelet Packet Decomposition are adopted for primary feature extraction before the quality measurement stage. The quality-filtered feature windows are then used to extract secondary features that are in turn classified using a linear discriminant classifier. The proposed system is tested using a publicly available EEG database and it shows that entropy filtering results in a significant improvement on performance. An average identification accuracy rate of more than 90% is achieved for 109 subjects using only eight electrodes, utilizing only the highest quality for each subject
- KonferenzbeitragSelecting discriminative features with discriminative multiple canonical correlationanalysis for multi-feature information fusion(BIOSIG 2013, 2013) Gao, Lei; Qi, Lin; Guan, LingIn this paper, it presents a novel approach for selecting discriminative features in multimodal information fusion based discriminative multiple canonical correlation analysis (DMCCA), which is the generalized form of canonical correlation analysis (CCA), multiple canonical correlation analysis (MCCA) and discriminative canonical correlation analysis (DCCA). The proposed approach identifies the discriminative features from the multi-feature in Fractional Fourier Transform (FRFT) domain, which are capable of simultaneously maximizing the within-class correlation and minimizing the between-class correlation, leading to better utilization of the multi-feature information and producing more effective pattern recognition results. The effectiveness of the introduced solution is demonstrated through extensive experimentation on a visual based emotion recognition problem.