Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | 2021 IEEE International Workshop on Information Forensics and Security (WIFS) |
| Publisher | IEEE |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Print) | 978-1-6654-1718-1 |
| DOIs | |
| Publication status | Published - 10 Dec 2021 |
| Event | 2021 IEEE International Workshop on Information Forensics and Security (WIFS) - Montpellier, France Duration: 7 Dec 2021 → 10 Dec 2021 |
Conference
| Conference | 2021 IEEE International Workshop on Information Forensics and Security (WIFS) |
|---|---|
| Period | 7/12/21 → 10/12/21 |
Keywords
- Forensics
- Conferences
- Fingerprint recognition
- Regulation
- Generators
- Security
Fields of Science and Technology Classification 2012
- 102 Computer Sciences