http://dl.gi.de/handle/20.500.12116/20081 2026-07-23T18:35:16Z 2026-07-23T18:35:16Z Olsen, Martin Aastrup Böckeler, Martin Busch, Christoph http://dl.gi.de/handle/20.500.12116/2303 2019-02-04T13:58:52Z 2015-01-01T00:00:00Z

Predicting Dactyloscopic Examiner Fingerprint Image Quality Assessments Olsen, Martin Aastrup; Böckeler, Martin; Busch, Christoph Brömme, Arslan; Busch, Christoph; Rathgeb, Christian; Uhl, Andreas We work towards a system which can assist dactyloscopic examiners in assessing the quality and decision value of a fingerprint image and eventually a fingermark. However when quality assessment tasks of datyloscopic examiners are replaced by automatic quality assessment then we need to ensure that the automatic measurement is in agreement with the examiner opinion. Under the assumption of such agreement, we can predict the examiner opinion. We propose a method for determining the examiner agreement on ordinal scales and show that there is a high level of agreement between examiners assessing the ground truth quality of fingerprints. With ground truth quality information on 749 fingerprints and using 10-fold cross validation we construct models using Support Vector Machines and Proportional Odds Logistic Re- gression which predicts median examiner quality assessments 35\% better than when using the prior class distribution.

2015-01-01T00:00:00Z Kotzerke, Johannes Davis, Stephen A. Hayes, Robert Spreeuwers, Luuk J. Veldhuis, Raymond N. J. Horadam, Kathy J. http://dl.gi.de/handle/20.500.12116/2304 2019-02-04T13:58:52Z 2015-01-01T00:00:00Z

Identification performance of evidential value estimation for fingermarks Kotzerke, Johannes; Davis, Stephen A.; Hayes, Robert; Spreeuwers, Luuk J.; Veldhuis, Raymond N. J.; Horadam, Kathy J. Brömme, Arslan; Busch, Christoph; Rathgeb, Christian; Uhl, Andreas Law enforcement agencies around the world use biometrics and fingerprints to solve and fight crime. Forensic experts are needed to record fingermarks at crime scenes and to ensure those captured are of evidential value. This process needs to be automated and streamlined as much as possible to improve efficiency and reduce workload. It has previously been demonstrated that is possible to estimate a fingermark's evidential value automatically for image captures taken with a mobile phone or other devices, such as a scanner or a high-quality camera. Here we study the relationship between a fingermark being of evidential value and its correct and certain identification and if it is possible to achieve identification despite the mark not having sufficient evidential value. Subsequently, we also investigate the influence the capture device used makes and if a mobile phone is an option worth considering. Our results show that automatic identification is possible for 126 of the 1 428 fin- , germarks captured by a mobile phone, of which 116 were marked as having evidential value by experts and 123 by an automated algorithm.

2015-01-01T00:00:00Z Hartloff, Jesse Mandal, Avradip Roy, Arnab http://dl.gi.de/handle/20.500.12116/2305 2019-02-04T13:58:52Z 2015-01-01T00:00:00Z

Privacy preserving technique for set-based biometric authentication using Reed-Solomon decoding Hartloff, Jesse; Mandal, Avradip; Roy, Arnab Brömme, Arslan; Busch, Christoph; Rathgeb, Christian; Uhl, Andreas In this work, we present a single-factor biometric authentication system that provides template security against an adversarial server while allowing errortolerant matching. Our approach is to secure templates represented as sets using errorcorrecting codes and Reed-Solomon decoding. To accomplish this, each element in the set is combined with a random codeword and a secret share is computed using the codeword and a Reed-Solomon based secret sharing scheme. These random codewords provide uncertainty for an attacker, while the genuine user can decode to the correct values for verification. Without a reading from the enrolling biometric the shares will appear random, thus protecting the users biometric. We show implementation results for this system on fingerprints using pairs of minutia points. Our system overcomes many common weaknesses for template security systems including replay attacks, malicious servers, eavesdroppers, and record multiplicity attacks.

2015-01-01T00:00:00Z Wild, Peter Hofbauer, Heinz Ferryman, James Uhl, Andreas http://dl.gi.de/handle/20.500.12116/2301 2019-02-04T13:58:52Z 2015-01-01T00:00:00Z

Segmentation-level fusion for iris recogntion Wild, Peter; Hofbauer, Heinz; Ferryman, James; Uhl, Andreas Brömme, Arslan; Busch, Christoph; Rathgeb, Christian; Uhl, Andreas This paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms.

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