Assessment of Synthetically Generated Mated Samples from Single Fingerprint Samples Instances
- Resource Type
- Conference
- Authors
- Kirchgasser, Simon; Kauba, Christof; Uhl, Andreas
- Source
- 2021 IEEE International Workshop on Information Forensics and Security (WIFS) Information Forensics and Security (WIFS), 2021 IEEE International Workshop on. :1-6 Dec, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Signal Processing and Analysis
Forensics
Conferences
Fingerprint recognition
Regulation
Generators
Security
fingerprint
synthetic sample generation
mated samples
performance evaluation
- Language
- ISSN
- 2157-4774
The availability of biometric data (here fingerprint samples) is a crucial requirement in all areas of biometrics. Due to recent changes in cross-border regulations (GDPR) sharing and accessing biometric sample data has become more difficult. An alternative way to facilitate a sufficient amount of test data is to synthetically generate biometric samples, which has its limitations. One of them is the generated data being not realistic enough and a more common one is that most free solutions are not able to generate mated samples, especially for fingerprints. In this work we propose a multi-level methodology to assess synthetically generated fingerprint data in terms of their similarity to real fingerprint samples. Furthermore, we present a generic approach to extend an existing synthetic fingerprint generator to be able to produce mated samples on the basis of single instances of non-mated ones which is then evaluated using the aforementioned multi-level methodology.