P245 - BIOSIG 2015 - Proceedings of the 14th International Conference of the Biometrics Special Interest Group
Auflistung nach:
Auflistung P245 - BIOSIG 2015 - Proceedings of the 14th International Conference of the Biometrics Special Interest Group nach Autor:in "Brömme, Arslan"
1 - 10 von 34
Treffer pro Seite
Sortieroptionen
- Editiertes BuchBIOSIG 2015(2015)
- KonferenzbeitragA comparative study on image hashing for document authentication(BIOSIG 2015, 2015) Klein, Dominik; Kruse, JanA digital seal is a cryptographically signed 2D barcode printed on a document to verify the document's authenticity and integrity. In order to secure a printed image against tampering, a compact image hash can be stored inside the barcode. We investigate and experimentally evaluate various methods from the areas of image hashing and face verification w.r.t. its appropriateness for such an image hash that is resistant to a print-scan transformation. Exhaustive experiments with genuine security paper show that compressed local binary patterns (LBPs) and feature extraction by DCT-II perform best in this setting.
- KonferenzbeitragContact-less Palm/Finger Vein Biometric(BIOSIG 2015, 2015) Sierro, Alexandre; Ferrez, Pierre; Roduit, PierreFinger and palm vein recognition, based on near infra-red images of the vein pattern of the finger or the palm, are promising biometric authentication methods. The main advantage of vein recognition over fingerprints is its touch-less nature, making it more robust to spoofing and more comfortable to the user. To this point, vein recognition has mainly been developed by private companies rather than by academic institutions and there are only a relatively limited number of scientific publications on the topic. This paper presents two palm vein and one finger vein imaging prototypes developed in our institution. An image database has also been acquired with each of these three prototypes.
- KonferenzbeitragCorneal topography: an emerging biometric system for person authentication(BIOSIG 2015, 2015) Kihal, Nassima; Polette, Arnaud; Chitroub, Salim; Brunette, Isabelle; Meunier, Jean
- KonferenzbeitragDiscarding low quality minutia cylinder-code pairs for improved fingerprint comparison(BIOSIG 2015, 2015) Izadi, M. Hamed; Drygajlo, AndrzejLocal minutiae descriptors such as Minutia Cylinder-Code (MCC) are becoming increasingly popular in modern fingerprint verification systems. The verification performance depends on the fingerprint image quality in global and local levels. Discarding part of the lowest quality samples based on quality measures is a universal approach being widely used for improving the performance of biometric recognition systems. In this work, we evaluate several different discarding methods to filter out low quality pairs of MCC descriptors using minutiae qualities, with the final aim of improving global comparison accuracy. Moreover, we propose an efficient MCC based fingerprint comparison method based on discarding the low quality elements from local similarity matrix. Our extensive experiments on three different databases (FVC2002 DB2, FVC2002 DB3 and FVC2004 DB3) show that 1) the proper discarding of low quality MCC pairs from local similarity matrix either independently or using pairwise measures can improve the MCC based comparison performance, 2) for the proposed discarding method, the quality of central minutiae is more efficient as cylinder quality measure than the average minutiae qualities in each descriptor.
- KonferenzbeitragDoes context matter for the performance of continuous authentication biometric systems? an empirical study on mobile devices(BIOSIG 2015, 2015) Mondal, Soumik; Bours, PatrickIn this paper we will show that context has an influence on the performance of a continuous authentication system. When context is considered we notice that the performance of the system improves by a factor of approximately 3. Even when testing and training are not based on exactly the same task, but on a similar task, we see an improvement of the performance over a system where the context is not included. In fact, we proof that the performance of the system depends on which particular kind of task is used for the training.
- KonferenzbeitragEEG biometrics for user recognition using visually evoked potentials(BIOSIG 2015, 2015) Das, Rig; Maiorana, Emanuele; Rocca, Daria La; Campisi, PatrizioElectroencephalographic signals (EEG) have been long supposed to contain features characteristic of each individual, yet a substantial interest for exploiting them as a potential biometrics for people recognition has only recently grown. The biggest advantages of EEG-based biometrics lie in its universality and security, while its major concerns are related to the acquisition protocol that can be inconvenient and time consuming. This paper investigates the use of EEG signals, elicited using visual stimuli, for the purpose of biometric recognition, and evaluates the performance obtained considering various frequency bands, different number of visual stimuli, and various subsets of time intervals after the stimuli presentation. An exhaustive set of experimental tests has been performed by employing EEG data of 50 different healthy subjects acquired in two different sessions, separated by one week time.
- KonferenzbeitragEvaluating the change in fingerprint directional patterns under variation of rotation and number of regions(BIOSIG 2015, 2015) Dorasamy, Kribashnee; Webb, Leandra; Tapamo, JulesDirectional patterns (DPs), which are formed by grouping regions of orientation fields falling within a specific range, vary under rotation and the number of regions. For fingerprint classification schemes, this can result in misclassification due to inconsistency of patterns. Knowing the optimal angle by which to rotate the image and the optimal number of orientation regions to divide it into can be beneficial in analysing specific properties of a class. Furthermore, the number of regions directly impacts singular point (SP) detection, therefore using the optimal number of regions prevents loss of SPs. However, no previous work justifies the use of a specific number of regions or angle of rotation. More so, no explicit studies have been conducted to establish the optimal number of regions or angle of rotation that result in gaining the most information from a pattern. Therefore, this research investigates the change in DPs under the variation of rotation and number of regions to determine which condition provides the best representation of the fingerprint that is less prone to noise and minimizes interclass variability issues with fewer possible patterns for each class. This can serve as a baseline for future works using DPs. The experiments were conducted on the Fingerprint Verification Competition (FVC) 2002 database (DB) 1a. It was found that using a small number of regions produces the most accurate SPs detection and increasing the region number to more than 6 regions drastically depletes the accuracy of SP detection. Furthermore, aligning the SPs of a fingerprint containing a single loop and delta, highlights the essential properties of a class better, with feError: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap Error: Illegal entry in bfrange block in ToUnicode CMap wer layouts for each class.
- KonferenzbeitragExploring gender prediction from iris biometrics(BIOSIG 2015, 2015) Fairhurst, Michael; Erbilek, Meryem; Da Costa-Abreu, MárjoryPrediction of gender characteristics from iris images has been investigated and some successful results have been reported in the literature, but without considering performance for different iris features and classifiers. This paper investigates for the first time an approach to gender prediction from iris images using different types of features (including a small number of very simple geometric features, texture features and a combination of geometric and texture features) and a more versatile and intelligent classifier structure. Our proposed approaches can achieve gender prediction accuracies of up to 90\% in the BioSecure Database.
- KonferenzbeitragExploring how user routine affects the recognition performance of a lock pattern(BIOSIG 2015, 2015) Wilde, Lisa De; Spreeuwers, Luuk; Veldhuis, RaymondTo protect an Android smartphone against attackers, a lock pattern can be used. Nevertheless, shoulder-surfing and smudge attacks can be used to get access despite of this protection. To combat these attacks, biometric recognition can be added to the lock pattern, such that the lock-pattern application keeps track of the way users draw the pattern. This research explores how users change the way they draw lock patterns over time and its effect on the recognition performance of the pattern. A lock-pattern dataset has been collected and a classifier is proposed. In this research the best result was obtained using the x- and y-coordinate as the user's biometrics. Unfortunately, in this paper it is shown that adding biometrics to a lock pattern is only an additional security that provides no guarantee for a secure lock pattern. It is just a small improvement over using a lock pattern without biometric identification.