antispoofing.crossdatabase 1.0.0

Using an automatic installer

Using pip is the easiest (shell commands are marked with a $ signal):

$ pip install antispoofing.crossdatabase

You can also do the same with easy_install:

$ easy_install antispoofing.crossdatabase

This will download and install this package plus any other required dependencies. It will also verify if the version of Bob you have installed is compatible.

This scheme works well with virtual environments by virtualenv or if you have root access to your machine. Otherwise, we recommend you use the next option.

Using zc.buildout

Download the latest version of this package from PyPI and unpack it in your working area. The installation of the toolkit itself uses buildout. You don’t need to understand its inner workings to use this package. Here is a recipe to get you started:

$ python bootstrap.py
$ ./bin/buildout

These 2 commands should download and install all non-installed dependencies and get you a fully operational test and development environment.

Crossdatabase test

The examples bellow show how to reproduce the performance using the inter-database protocol.

For each countermeasure trained and tuned with the Replay Attack Database, to get the performance using the test set of the Casia FASD, just type:

$ ./bin/crossdb_result_analysis.py --scores-dir <scores_replay_countermeasure_directory> -d replay -t casias_fasd:

For each countermeasure trained and tuned with the Casia FASD, to get the performance using the test set of the Replay Attack Database, just type:

$ ./bin/crossdb_result_analysis.py --scores-dir <scores_casia_countermeasure_directory> -d casia_fasd -t replay

Training all data

To get the performance using a countermeasure trained and tuned with both databases (Replay Attack Database and Casia FASD) just type:

To report the results using the Replay Attack Database:

$ ./bin/crossdb_result_analysis.py --scores-dir <scores_all_countermeasures_directory> -d all -t replay

To report the results using the Casia FASD:

$ ./bin/crossdb_result_analysis.py --scores-dir <scores_all_countermeasures_directory> -d all -t casia_fasd

Framework

For each countermeasures, to get the performance using the Score Level Fusion based Framework just type:

To report the results using the Replay Attack Database:

$ ./bin/crossdb_fusion_framework.py --scores-dir <scores_trained_with_replay> <scores_trained_with_casia> -d all -t replay --normalizer MinMaxNorm --fusion-algorithm SUM

To report the results using the Casia FASD:

$ ./bin/crossdb_fusion_framework.py --scores-dir <scores_trained_with_casia> <scores_trained_with_replay> -d all -t casia_fasd --normalizer MinMaxNorm --fusion-algorithm SUM