P212 - BIOSIG 2013 - Proceedings of the 12th International Conference of the Biometrics Special Interest Group
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- KonferenzbeitragVideo-based fingerphoto recognition with anti-spoofing techniques with smartphone cameras(BIOSIG 2013, 2013) Stein, Chris; Bouatou, Vincent; Busch, ChristophThis work is concerned with the acquisition of fingerprints samples on smartphones with the built-in smartphone camera. A novel approach to capture multiple fingerphotos in a videostream with a smartphone camera and the processing of the photos for the finger recognition is discussed in this paper. The proposed technique offers a convenient and efficient way to capture multiple samples of a biometric instance in a short time frame. Due the fact that fingerphotos can be easily replicated with low effort (e.g. print outs with an ordinary printer) and thus are vulnerable to presentation attacks, anti-spoofing algorithms were developed to detect such spoof attempts. The algorithms for the detection and segmentation of the finger as well the preprocessing of the photo with graphical operations and anti-spoofing were implemented in a prototype as application for the Android operating system. User tests are performed to evaluate the usability and to create a database of biometric samples for offline evaluation of the recognition performance. Further tests are done with diverse artefacts such as printed finger images, fake fingers of gelatin, gummy and silicon as well finger replay videos to measure the resistance of the developed solution against presentation attacks.
- 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.
- KonferenzbeitragQuality driven iris recognition improvement(BIOSIG 2013, 2013) Cremer, Sandra; Lemperiere, Nadege; Dorizzi, Bernadette; Garcia-Salicetti, SoniaThe purpose of the work presented in this paper is to adapt the feature extraction and matching steps of iris recognition to the quality of the input images. To this end we define a GMM-based global quality metric associated to a pair of normalized iris images. It quantifies the amount of artifact in these images as well as the amount of texture in artifact-free regions. First we use this metric to adjust, for each pair of irises, the proportion of the normalized image selected on a local quality criteria for feature extraction. This approach is tested with two matching techniques: one performs a bit to bit comparison of binary feature vectors and the other one computes local cross-correlations between real valued vectors. We show that our approach is effective with both techniques. Then we use our metric to choose the matching technique that is best adapted to each image pair in order to make a good compromise between accuracy and speed.
- KonferenzbeitragSimulated annealing attack on certain fingerprint authentication systems(BIOSIG 2013, 2013) Pashalidis, AndreasThis paper describes a simple and generic attack against minutiae-based fingerprint authentication systems. The aim of the attack is to construct a fingerprint minutiae template, compliant to ISO/IEC standards, that matches a fixed but unknown target fingerprint. Our attack is expected to be most effective against systems that employ vicinity-based matching algorithms, i.e. systems that divide fingerprints into multiple regions and then compute similarity over these regions. The effectiveness of our attack is experimentally demonstrated against the recently proposed `Protected Minutiae Cylinder Code' (PMCC) scheme.
- KonferenzbeitragAbsolute fingerprint pre-alignment in minutiae-based cryptosystems(BIOSIG 2013, 2013) Tams, BenjaminMost biometric cryptosystems that have been proposed to protect fingerprint minutiae make use of public alignment helper data. This, however, has the inadvertent effect of information leakage about the protected templates. A countermeasure to avoid auxiliary alignment data is to protect absolutely pre-aligned fingerprints. As a proof of concept, we run performance evaluations of a minutiae fuzzy vault with an automatic method for absolute pre-alignment. Therefore, we propose a new method for estimating a fingerprint's directed reference point by modeling the local orientation around the core as a tented arch.1
- Editiertes BuchBIOSIG 2013(2013)
- KonferenzbeitragVolumetric fingerprint data analysis using optical coherence tomography(BIOSIG 2013, 2013) Sousedik, Ctirad; Breithaupt, Ralph; Busch, ChristophThe increasing usage of fingerprint biometrics as a security technology requires the biometric systems to be resistant against moderate or even high attack potential. To date, state-of-the-art fingerprint sensors can be deceived by using an accurate imitation of the ridge/valley pattern of an enrolled fingerprint that can be produced utilizing low-cost, commonly available materials and techniques. The structure of high-resolution 3D volumetric scans of fingertips, acquired by using the Optical Coherence Tomography (OCT), has been analyzed by this work so that a Presentation Attack Detection method could be developed that would render the artefact production process extremely difficult or even practically impossible.
- 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.
- KonferenzbeitragAutomatic landmark detection and face recognition for side-view face images(BIOSIG 2013, 2013) Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N. J.In real-life scenarios where pose variation is up to side-view positions, face recognition becomes a challenging task. In this paper we propose an automatic sideview face recognition system designed for home-safety applications. Our goal is to recognize people as they pass through doors in order to determine their location in the house. Here, we introduce a recognition method, where we detect facial landmarks automatically for registration and identify faces. We test our system on side-view face images from CMU-Multi PIE database. We achieve 95 95% accuracy on detecting . landmarks, and 89 04% accuracy on identification. .
- 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.