Implementation of the local and global unlinkability metrics for biometric template protection systems evaluation proposed in [TIFS18].
This work is licensed under license agreement provided by Hochschule Darmstadt (h_da-License).
usage: evaluateUnlinkability.py [-h] [--omega [OMEGA]] [--nBins [NBINS]] [--figureTitle [FIGURETITLE]] [--legendLocation [LEGENDLOCATION]] matedScoresFile nonMatedScoresFile figureFile Evaluate unlinkability for two given sets of mated and non-mated linkage scores. positional arguments: matedScoresFile filename for the mated scores nonMatedScoresFile filename for the non-mated scores figureFile filename for the output figure optional arguments: -h, --help show this help message and exit --omega [OMEGA] omega value for the computations, if none provided, omega = 1 --nBins [NBINS] number of bins for the computations, if none provided, nBins = 100 --figureTitle [FIGURETITLE] title for the output figure --legendLocation [LEGENDLOCATION] legend location
Input: at least 3 score files (mated and non-mated score examples provided), and optionally other parameters of the computation and the formatting of the figure obtained as output.
The score files are loaded with the built-in function numpy.fromfile(). An example in hdf5 format has been provided, but other formats, such as a txt file with all scores separated by blank spaces or one score per row, can be also used.
Output: figure with score distributions, point-wise and global unlinkability metric results.
More details in:
- [TIFS18] M. Gomez-Barrero, J. Galbally, C. Rathgeb, C. Busch, "General Framework to Evaluate Unlinkability in Biometric Template Protection Systems", in IEEE Trans. on Informations Forensics and Security, vol. 3, no. 6, pp. 1406-1420, June 2018.
Please remember to reference article [TIFS18] on any work made public, whatever the form, based directly or indirectly on these metrics.