Ctirad Sousedik

Ctirad Sousedik

Ph.D. started in: 2012
Year of graduation: 2018
COINS consortium member: Norwegian University of Science and Technology
Supervised by: Christoph Busch
Links:
Research area: Authentication and Biometrics
Project title: Fake Resistant Fingerprint Biometrics
Project description: Fingerprint sensing devices are vulnerable against fake representations of the fingerprint. Fake fingerprints made of artificial materials can be used to circumvent a fingerprint system. Main research topic of this project is to develop a reliable fingerprint liveness detection method based on the Optical Coherence Tomography technology. The OCT allows to obtain 3D volumetric representations of the fingerprint up to depth of 2-3 mm. If an automatic method could be developed that would validate the structure of a genuine living finger, the fake production process would be extremely difficult. In addition, the thesis focuses on detection of fingerprint alterations – voluntary changes to the fingerprint pattern in order to avoid identification.

1. Ctirad Sousedik, Ralph Breithaupt (2017). Full-fingerprint Volumetric Subsurface Imaging using Fourier-Domain Optical Coherence Tomography
2. Ctirad Sousedik, Ralph Breithaupt, Patrick Bours (2017). Classification of Fingerprints Captured Using Optical Coherence Tomography
3. Ralph Breithaupt, Ctirad Sousedik, Sven Meissner (2015). Full fingerprint scanner using optical coherence tomography
4. John Ellingsgård, Ctirad Sousedik, Christoph Busch (2014). Detecting fingerprint alterations by orientation field and minutiae orientation analysis
5. Niclas Overgaard, Ctirad Sousedik, Christoph Busch (2014). Eulerian Video Magnification for Fingerprint Liveness Detection
6. Ctirad Sousedik, Christoph Busch (2014). Presentation attack detection methods for fingerprint recognition systems: a survey
7. Ctirad Sousedik, Christoph Busch (2014). Quality of Fingerprint Scans captured using Optical Coherence Tomography
8. Ctirad Sousedik, Ralph Breithaupt, Christoph Busch (2013). Volumetric Fingerprint Data Analysis using Optical Coherence Tomography