Biometrics and Machine Learning Group
Latest news
We are pleased to announce that Mateusz Trokielewicz defended (with honors) his doctoral dissertation entitled „Iris Recognition Methods Resistant to Biological Changes in the Eye” , supervised by prof. Czajka and prof. Pacut, on the 18th of July, 2019.
Iris scanner can distinguish dead eyeballs from living ones: MIT Technology Review reports on our recent developements in the field of presentation attack detection for cadaver irises.
We are pleased to announce that Mateusz Trokielewicz received the EAB European Biometrics Research Award 2016 for research on iris recognition reliability including template aging, influence of eye diseases and post-mortem recognition.
Is That Eyeball Dead or Alive? Adam Czajka discusses the prevention of iris sensors accepting the use of a high-resolution photo of an iris or, in a grislier scenario, an actual eyeball. For full article, please see IEEE Spectrum.
wersja polska
Biometrics Scientific Club
President |
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Mateusz Trokielewicz Biometrics and Machine Learning Group Institute of Control and Computation Engineering Warsaw University of Technology e-mail: M.Trokielewicz [at] stud.elka.pw.edu.pl, WWW room: 558 |
Vice President |
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Monika Selegrat e-mail: KoloBiometrii [at] gmail.com |
Secretary |
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Radek Białobrzeski e-mail: KoloBiometrii [at] gmail.com |
Mentor |
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Adam Czajka Biometrics and Machine Learning Group Institute of Control and Computation Engineering Warsaw University of Technology |
Biometrics Scientific Club gathers undergraduate and graduate students interested in gaining experience and expertise concerning biometric techniques, algorithms, devices and more. Our community is involved in stand-alone, homebrew projects, as well as popularizing biometrics at science fairs and other events. Current projects include secure iris solutions for mobile and remote biometric authentication using fingerprint recognition.
Project: Secure iris recognition goes mobile
In the age of modern, hyperconnected society that increasingly relies on mobile devices, implementing a secure, fast and reliable iris recognition presents new challenges. How does one make it easy to use, and at the same time safe from counterfeiting? This project focuses on implementing biometric recognition for iOS, that employs an open-source matching technology, together with a custom-designed liveness testing mechanism for a reliable Presentation Attack Detection (PAD).
Project: Client-server remote fingerprint authentication
Based on a typical "client-server" architecture, this educational project brings together coding skills and IT system design with biometric expertise. Our aim is to create a biometric system employing fingerprint recognition for remote authentication using client devices for sample collection and a server machine to process the data (using a selected open-source methodology) and compare against records stored in the central database, providing authentication that can later be translated e.g., to an access to restricted assets.
For more up-to-date information, visit our Facebook page (do not hesitate to contact us, even if you don't speak Polish - we do speak English and try to update our page in both languages :-)
https://www.facebook.com/kolonaukowebiometrii
Finally, follow us on Twitter and tweet to us @KoloBiometrii:
Contact us
Institute of Control
and Computation Engineering
Warsaw University of Technology
ul. Nowowiejska 15/19
00-665 Warsaw, Poland
phone: +48 (22) 234 73 97
