P315 - BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group
Auflistung nach:
Auflistung P315 - BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group nach Titel
1 - 10 von 33
Treffer pro Seite
Sortieroptionen
- KonferenzbeitragAssessment of Sensor Ageing-Impact in Air Travelled Fingerprint Capturing Devices(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Kauba, Christof; Kirchgasser, Simon; Jöchl, Robert; Uhl, AndreasBiometric recognition performance is affected by many factors, like varying acquisition conditions or ageing related effects, commonly denoted as biometric template ageing. Image sensor ageing, being part of biometric template ageing and a sub-field of image and video forensics, leads to defective pixels due to cosmic radiation, depending on the altitude. So far, image sensor ageing has only been a peripheral target in fingerprint research. We investigate the impact of image sensor ageing on various fingerprint capturing devices, including optical, capacitive and thermal ones. We established a fingerprint ageing dataset utilising 10 capturing devices which travelled on an air-plane for 127 days (to increase the number of developed defects). By evaluating the samples captured prior to their travel and afterwards using several state-of-the-art fingerprint quality metrics as well as minutiae-based fingerprint recognition systems we quantify the effect of image sensor ageing on fingerprint recognition. Furthermore, by employing a defect detection technique we quantify the number of defects developed during that period.
- KonferenzbeitragBiometric Recognition in a Multi-sample Multi-Subject Facial Image Database: The 1:M:N System Model(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Halfen, DeWayne; Rajaraman, Srinivasan; Wayman, James L.Over the last 50 years, biometric recognition has advanced from localized “identity verification” applications [GU77][RY74] to include large-scale systems in which “a determination is made as to the identity of an individual independently of any information supplied by the individual” [GU77]. Models for estimating and expressing system error rates (both false matches and false non-matches) have been largely limited to so-called “1-to-1” and “1-to-N” systems in which each identity is represented by only one enrolled reference [Gr21]. In this paper, we create a highly simplified simulation model for a common current situation in which each known identity record has multiple stored references. We call this the “1:M:N” model and show that both DET and CMC performance depend upon the number of identities and images per identity, not simply the total number of references images, as usually assumed. Although trialed here on very simple decision policies, this model will be extended in future work to more complex decision criteria.
- KonferenzbeitragBIOSIG 2021 - Complete Volume(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021)
- KonferenzbeitragBloom Filter vs Homomorphic Encryption: Which approach protects the biometric data and satisfies ISO/IEC 24745?(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Bassit, Amina; Hahn, Florian; Zeinstra, Chris; Veldhuis, Raymond; Peter, AndreasBloom filter (BF) and homomorphic encryption (HE) are popular modern techniques used to design biometric template protection (BTP) schemes that aim to protect the sensitive biometric information during storage and the comparison process. However, in practice, many BTP schemes based on BF or HE violate at least one of the privacy requirements of the international standard ISO/IEC 24745: irreversibility, unlinkability and confidentiality. In this paper, we investigate the state-of-the-art BTP schemes based on these two approaches and assess their relative strengths and weaknesses with respect to the three requirements of ISO/IEC 24745. The results of our investigation showed that the choice between BF and HE depends on the setting where the BTP scheme will be deployed and the level of trustworthiness of the parties involved in processing the protected template. As a result, HE enhanced by verifiable computation techniques can satisfy the privacy requirements of ISO/IEC 24745 in a trustless setting.
- KonferenzbeitragCurricular SincNet: Towards Robust Deep Speaker Recognition by Emphasizing Hard Samples in Latent Space(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Chowdhury, Labib; Kamal, Mustafa; Tasnim, Najia; Mohammed, NabeelDeep learning models have become an increasingly preferred option for biometric recognition systems; such as speaker recognition. SincNet, a deep neural network architecture gained popularity in speaker recognition tasks, due to its use of parameterized sinc functions that allow it to work directly on the speech signal. The original SincNet architecture uses the softmax loss which may not be the most suitable choice for recognition-based tasks, as such loss functions do not impose inter-class margins nor does it differentiate between easy and hard training samples. Curriculum learning, particularly those leveraging angular margin-based losses has proven to be very successful in other biometric applications such as face recognition. The advantage of such a curriculum learning-based techniques is that it will impose inter-class margins as well as taking to account easy and hard samples. In this paper, we propose Curricular SincNet (CL-SincNet), an improved SincNet model where we use a curricular loss function to do the training on the SincNet architecture. The proposed model is evaluated on multiple datasets using intra-dataset and inter-dataset evaluation protocol. In both settings, the model performs competitively with other previously published work and in the case of inter-dataset testing, it achieves the best overall results with a reduction of 4% error rate compare to SincNet and other published work.
- KonferenzbeitragDetecting Sexual Predatory Chats by Perturbed Data and Balanced Ensembles Effects(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Borj, Parisa Rezaee; Raja, Kiran; Bours, PatrickSecuring the safety of the children on online platforms is critical to avoid the mishaps of them being abused for sexual favors, which usually happens through predatory conversations. A number of approaches have been proposed to analyze the content of the messages to identify predatory conversations. However, due to the non-availability of large-scale predatory data, the stateof-the-art works employ a standard dataset that has less than 10% predatory conversations. Dealing with such heavy class imbalance is a challenge to devise reliable predatory detection approaches. We present a new approach for dealing with class imbalance using a hybrid sampling and class re-distribution to obtain an augmented dataset. To further improve the diversity of classifiers and features in the ensembles, we also propose to perturb the data along with augmentation in an iterative manner. Through a set of experiments, we demonstrate an improvement of 3% over the best stateof-the-art approach and results in an F1-score of 0.99 and an Fβ of 0.94 from the proposed approach.
- KonferenzbeitragThe effect of face morphing on face image quality(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Fu, Biying; Spiller, Noémie; Chen, Cong; Damer, NaserFace morphing poses high security risk, which motivates the work on detection algorithms, as well as on anticipating novel morphing approaches. Using the statistical and perceptual image quality of morphed images in previous works has shown no clear correlation between the image quality and the realistic appearance. This motivated our study on the effect of face morphing on image quality and utility, we, therefore, applied eight general image quality metrics and four facespecific image utility metrics. We showed that MagFace (face utility metric) shows a clear difference between the bona fide and the morph images, regardless if they were digital or re-digitized. While most quality and utility metrics do not capture the artifacts introduced by the morphing process. Acknowledged that morphing artifacts are more apparent in certain areas of the face, we further investigated only these areas, for instance, tightly cropped face, nose, eyes, and mouth regions. We found that especially close to the eyes and the nose regions, using general image quality metrics as MEON and dipIQ can capture the image quality deterioration introduced by the morphing process.
- KonferenzbeitragEmerging biometric modalities and their use: Loopholes in the terminology of the GDPR and resulting privacy risks(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Bisztray, Tamás; Gruschka, Nils; Bourlai, Thirimachos; Fritsch, LotharTechnological advancements allow biometric applications to be more omnipresent than in any other time before. This paper argues that in the current EU data protection regulation, classification applications using biometric data receive less protection compared to biometric recognition. We analyse preconditions in the regulatory language and explore how this has the potential to be the source of unique privacy risks for processing operations classifying individuals based on soft traits like emotions. This can have high impact on personal freedoms and human rights and, therefore, should be subject to data protection impact assessment.
- KonferenzbeitragEvaluation on Biometric Accuracy Estimation Using Generalized Pareto (GP) Distribution(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Yamada, Shigefumi; Matsunami, TomoakiThe accuracy of biometric authentication technology is becoming more sophisticated with its progress. For this reason, a huge number of biometric samples are required for accuracy evaluation, and the increased collection cost is an issue for biometric vendors. This work establishes a biometric accuracy estimation method using an extreme value theory to reduce the collection cost. It also explains the estimation procedure of false match rate using the generalized Pareto distribution and shows results applied to the face, gait, and voice comparison score data with an estimation effect of about 5–10 times. We investigate the criteria for the applicability of extremum statistics through application cases.
- KonferenzbeitragFingermark Quality Assessment: An Open-Source Toolbox(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Oblak, Tim; Haraksim, Rudolf; Beslay, Laurent; Peer, PeterFingermark quality assessment is an important step in a forensic fingerprint identification process. Often done in the scope of criminal investigation, it is performed by trained fingerprint examiners whose quality assessment can be rather subjective. The goal of this work is to develop an automated fingermark quality assessment tool, which would assist the fingermark examiners in their work. In this paper, we present a fast, open-source, and well documented fingermark quality assessment toolbox, which contains more than 20 algorithms for feature extraction, segmentation, and enhancement of fingermark images. We demonstrate the utility of the toolbox by assembling a feature vector and training various baseline machine learning models, capable of predicting the quality of fingermark images with high accuracy.