Package: bob.palmvein
The Palmvein Recognition LibraryWelcome to the Palm vein Recognition Library based on Bob.
This library is designed to perform a fair comparison of palm vein recognition algorithms.
It contains scripts to execute various kinds of palm vein recognition experiments on a variety of palm vein image databases, and running the help is as easy as going to the command line and typing:$ bin/palmveinverify.py --helpAboutThis library is developed at theBiometrics groupat theIdiap Research Institute.
The PalmVeinRecLib is designed to run palm vein recognition experiments in a comparable and reproducible manner.NoteWhen you are working atIdiap, you might get a version of the PalmVeinRecLib, where all paths are set up such that you can directly start running experiments.
OutsideIdiap, you need to set up the paths to point to your databases, please check the documentation on how to do that.DatabasesTo achieve this goal, interfaces to many publicly available facial image databases are contained, and default evaluation protocols are defined, e.g.:CASIA Multi-Spectral Palmprint Database [http://biometrics.idealtest.org/dbDetailForUser.do?id=6]VERA Palm vein Database [http://www.idiap.ch/scientific-research/resources]AlgorithmsTogether with that, a broad variety of traditional and state-of-the-art palm vein recognition algorithms such as:Local Binary Pattern Histogram Sequences[ZSG+05]is provided.
Furthermore, tools to evaluate the results can easily be used to create scientific plots, and interfaces to run experiments using parallel processes or an SGE grid are provided.ExtensionsOn top of these already pre-coded algorithms, the PalmVeinRecLib provides an easy Python interface for implementing new image preprocessors, feature types, palm vein recognition algorithms or database interfaces, which directly integrate into the palmvein recognition experiment.
Hence, after a short period of coding, researchers can compare their new invention directly with already existing algorithms in a fair manner.References[ZSG+05]W. Zhang, S. Shan, W. Gao, X. Chen and H. Zhang.Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition. Computer Vision, IEEE International Conference on, 1:786-791, 2005.InstallationTo download the PalmVeinRecLib, please go tohttp://pypi.python.org/pypi/bob.palmvein, click on thedownloadbutton and extract the .zip file to a folder of your choice.The PalmVeinRecLib is a satellite package of the free signal processing and machine learning libraryBob.
These two dependencies have to be downloaded manually, as explained in the following.BobYou will need a copy of Bob in version 2.0 or newer to run the algorithms.
Please downloadBobfrom its webpage.
After downloading, you should go to the console and write:$ python bootstrap-buildout.py
$ bin/buildoutThis will download all required packages and install them locally.
If you don’t want all the database packages to be downloaded, please remove the bob.db.[database] lines from theeggssection of the filebuildout.cfgin the main directory before calling the three commands above.Test your installationTo verify that your installation worked as expected, you might want to run our test utilities:$ bin/nosetestsUsually, all tests should pass, if you use the latest packages ofBob.
With other versions ofBob, you might find some failing tests, or some errors might occur.Cite our paperIf you use the PalmVeinRecLib in any of your experiments, please cite the following paper:@inproceedings{Tome_ICB2015-SpoofingPalmvein,
       author = {Tome, Pedro and Marcel, S{\'{e}}bastien},
     projects = {Idiap, BEAT, TABULA RASA},
        month = may,
        title = {On the Vulnerability of Palm Vein Recognition to Spoofing Attacks},
    booktitle = {The 8th IAPR International Conference on Biometrics (ICB)},
         year = {2015},
          pdf = {http://publications.idiap.ch/downloads/papers/2015/Tome_ICB2015-SpoofingPalmvein.pdf}
          }