Hello,
We'd like to announce the immediate availability of bob.bio.vein - a set of algorithms and baselines for vein recognition using near-infrared imagery.
bob.bio.vein includes:
1. Database interfaces to UTFVP and Vera Fingervein
2. 3 baselines based on Repeated Line Tracking (Miura 2004), Maximum Curvature (Miura 2005) and Wide Line Detector (Huang 2010)
3. A number of preprocessing and matching strategies beyond the baselines above
4. Uses bob.bio.base as a base open-science framework so you can build your own systems on the top of the existing infrastructure
This version includes fixes and optimizations to Pedro's original work, including a bug fix on "Maximum Curvature" and sensible speed-ups to our implementation of Miura Matching. If you used "xbob.fingervein" before, we advise you take this new implementation to a spin.
Then, activate your environment and install bob.bio.vein alongside database interfaces you may be interested on:
(bob3) $ conda install bob.bio.vein bob.db.utfvp bob.db.verafinger
If you make use of this package on your paper, make sure to cite our original work at:
@inproceedings{Tome_IEEEBIOSIG2014,
author = {Tome, Pedro and Vanoni, Matthias and Marcel, S{\'{e}}bastien},
keywords = {Biometrics, Finger vein, Spoofing Attacks},
month = sep,
title = {On the Vulnerability of Finger Vein Recognition to Spoofing},
booktitle = {IEEE International Conference of the Biometrics Special Interest Group (BIOSIG)},
series = {},
volume = {},
year = {2014},
pages = {},
location = {Darmstadt, Germay},
url = {http://publications.idiap.ch/index.php/publications/show/2910}
}
Please let us know of any feedback or input you may have,
Best, Andre
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