Package: antispoofing.evaluation
This package provides methods for evaluation of biometric verification systems under spoofing attacks. The evaluation is based on the Expected Performance and Spoofability Curve (EPSC). Using this package, you can compute thresholds based on EPSC, compute various error rates and plot various curves related to EPSC.Besides providing methods for plotting EPSC within your own scripts, this package brings several scripts that you can use to evaluate your own verification system (fused with an anti-spoofing system or not) from several perspectives. For example, you can:evaluate the threshold of a classification system on the development setapply the threshold on an evaluation or any other set to compute different error ratesplot score distributionsplot different performance curves (DET, EPC and EPSC)Furthermore, you can generate hypothetical data and use them to exemplify the above mentioned functionalities.If you use this package and/or its results, please cite the following
publication:Our original paper on biometric evaluation (title, pdf and bibtex to be announced soon):@ARTICLE{Chingovska_IEEETIFS_2014,
   author = {Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
   title = {Biometrics Evaluation Under Spoofing Attacks},
   journal = {IEEE Transactions on Information Forensics and Security},
   year = {2014},
}Bobas the core framework used to run the experiments:@inproceedings{Anjos_ACMMM_2012,
    author = {A. Anjos AND L. El Shafey AND R. Wallace AND M. G\"unther AND C. McCool AND S. Marcel},
    title = {Bob: a free signal processing and machine learning toolbox for researchers},
    year = {2012},
    month = oct,
    booktitle = {20th ACM Conference on Multimedia Systems (ACMMM), Nara, Japan},
    publisher = {ACM Press},
}If you wish to report problems or improvements concerning this code, please
contact the authors of the above mentioned papers.InstallationNoteIf you are reading this page through our GitHub portal and not through PyPI,
notethe development tip of the package may not be stableor become
unstable in a matter of moments.Go tohttp://pypi.python.org/pypi/antispoofing.evaluationto download the latest
stable version of this package. Then, extract the .zip file to a folder of your choice.Theantispoofing.evaluationpackage is a satellite package of the free signal processing and machine learning libraryBob. This dependency has to be downloaded manually. This version of the package depends onBobversion 2 or greater. To installpackages of Bob, please read theInstallation Instructions. ForBobto be able to work properly, some dependent Bob packages are required to be installed. Please make sure that you have read the Dependencies for your operating system.The most simple solution is to download and extractantispoofing.evaluationpackage, then to go to the console and write:$ cd antispoofing.evaluation
$ python bootstrap-buildout.py
$ bin/buildoutThis will download all required dependentBoband other packages and install them locally.Using the packageAfter instalation of the package, go to the console and type:$ ./bin/sphinx-build doc sphinxNow, the full documentation of the package, including a User Guide, will be availabe insphinx/index.html.ProblemsIn case of problems, please contactivana.chingovska@idiap.ch