at the `Idiap Research Institute <http://www.idiap.ch>`_. The vein recognition
library is designed to run vein recognition experiments in a comparable and
...
...
@@ -46,7 +46,7 @@ Databases
To achieve this goal, interfaces to some publicly available vein image
databases are contained, and default evaluation protocols are defined, e.g.:
- UTFVP - University of Twente Finger Vein Database [http://website]
- UTFVP - University of Twente Finger Vein Database [http://www.sas.ewi.utwente.nl/]
- VERA Finger vein Database [http://www.idiap.ch/scientific-research/resources]
...
...
@@ -56,9 +56,9 @@ Algorithms
Together with that, implementations of a variety of traditional and
state-of-the-art vein recognition algorithms are provided:
* Maximum Curvature [MNM+05]_
* Repeated Line Tracking [MNM+04]_
* Wide Line Detector [HDLTL+10]_
* Maximum Curvature [MNM05]_
* Repeated Line Tracking [MNM04]_
* Wide Line Detector [HDLTL10]_
Tools to evaluate the results can easily be used to create scientific plots. We
also provide handles to run experiments using parallel processes or an SGE
...
...
@@ -70,37 +70,46 @@ Extensions
On top of these already pre-coded algorithms, the vein recognition library
provides an easy Python interface for implementing new image preprocessors,
feature types, finger vein recognition algorithms or database interfaces, which
directly integrate into the fingervein recognition experiment. Hence, after a
short period of coding, researchers can compare their new invention directly
with already existing algorithms in a fair manner.
feature types, vein recognition algorithms or database interfaces, which
directly integrate into the vein recognition experiment. Hence, after a short
period of coding, researchers can compare new ideas directly with already
existing algorithms in a fair manner.
References
----------
.. [MNM+05] *N. Miura, A. Nagasaka, and T. Miyatake*. **Extraction of Finger-Vein Pattern Using Maximum Curvature Points in Image Profiles**. Proceedings on IAPR conference on machine vision applications, 9, pp. 347--350, 2005.
.. [MNM05] *N. Miura, A. Nagasaka, and T. Miyatake*. **Extraction of Finger-Vein Pattern Using Maximum Curvature Points in Image Profiles**. Proceedings on IAPR conference on machine vision applications, 9, pp. 347--350, 2005.
.. [MNM+04] *N. Miura, A. Nagasaka, and T. Miyatake*. **Feature extraction of finger vein patterns based on repeated line tracking and its application to personal identification**. Machine Vision and Applications, Vol. 15, Num. 4, pp. 194--203, 2004.
.. [MNM04] *N. Miura, A. Nagasaka, and T. Miyatake*. **Feature extraction of finger vein patterns based on repeated line tracking and its application to personal identification**. Machine Vision and Applications, Vol. 15, Num. 4, pp. 194--203, 2004.
.. [HDLTL+10] *B. Huang, Y. Dai, R. Li, D. Tang and W. Li*. **Finger-vein authentication based on wide line detector and pattern normalization**. Proceedings of the 20th International Conference on Pattern Recognition (ICPR), 2010.
.. [HDLTL10] *B. Huang, Y. Dai, R. Li, D. Tang and W. Li*. **Finger-vein authentication based on wide line detector and pattern normalization**. Proceedings of the 20th International Conference on Pattern Recognition (ICPR), 2010.
Installation
------------
To download the finger vein library, go to
http://pypi.python.org/pypi/bob.bio.vein click on the **download** button and
extract the .zip file to a folder of your choice.
The latest version of the vein recognition library can be installed with our
`Conda-based builds`_. Once you have installed Bob_, just go on and install
this package using the same installation mechanism.
The FingerVeinRecLib is a satellite package of the free signal processing and
machine learning library Bob_. We advise you install Bob first and then use
that installation to bootstrap the installation of this package::
$ python bootstrap.py
$ bin/buildout
Development
-----------
This will download any further dependencies and install them locally.
In order to develop the latest version of this package::
