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.
Iris Localization using Active Contours
Method proposed by W. Gutfeter in her engineering dissertation (under supervision of A.Czajka) was a step toward creating more accurate iris localization algorithm. In comparison to the classic methods deriving from the Daugman's algorithm [1], iris contours were modelled by the closed curves and not by the circles. Estimation of contours was conducted using Level Set approach introduced by Osher and Sethian in [2].
For each image of the eye an array with actual values of the level-set function φ was created – so called φ-map. It was assumed that the contour leads through the points at which φ function changes its sign (0-level set). Initial positon of contour was established as a circle laying inside the area of the pupil. Then values of the φ-map were updated iteratively according to the procedure described by the equation.
where ν and κ are additonal parameters of the evolution (speed and curvature).
Update causes the contour to move toward a desired position – they should be attracted by the areas in the image with a high gradient of the intensity. By fine-tuning the parameters of update function the shape of the contour could be controlled – it can be more elastic or more circle-like. One of the improvements introduced in the project was to process the image in the coarse-to-fine strategy: resolution of the image was increased while approaching the final solution.
Method was evaluated on modified Bath Iris Database with hand-drawn masks for iris and pupil. It gained almost 3 times higher accuracy (defined by the common geometric area of the result and the reference mask) than other two methods based on Daugman's algorithm.
Publication
W.Gutfeter, "Lokalizacja tęczówki metodą Aktywnych Konturów (eng. Iris localization using Active Contours)", engineering thesis, supervisor: A. Czajka, 2010, Warsaw University of Technology