Commit e49fe271 authored by André Anjos's avatar André Anjos 💬

Documentation is now compiling cleanly

parent 38ac1db8
......@@ -18,6 +18,16 @@ class MiuraMatch (Algorithm):
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
Parameters:
ch (int, Optional): Maximum search displacement in y-direction. Different
defult values based on the different features.
cw (int, Optional): Maximum search displacement in x-direction. Different
defult values based on the different features.
"""
def __init__(self,
......
......@@ -50,11 +50,11 @@ class FingerCrop (Preprocessor):
0.2 in a float image with values between 0 and 1).
fingercontour (str, Optional): Select between three finger contour
implementations: leemaskMod, leemaskMatlab or konomask. (From Pedro Tome:
the option ``leemaskMatlab`` was just implemented for testing purposes so
we could compare with MAT files generated from Matlab code of other
authors. He only used it with the UTFVP database, using ``leemaskMod``
with that database yields slight worse results.)
implementations: ``"leemaskMod"``, ``"leemaskMatlab"`` or ``"konomask"``.
(From Pedro Tome: the option ``leemaskMatlab`` was just implemented for
testing purposes so we could compare with MAT files generated from Matlab
code of other authors. He only used it with the UTFVP database, using
``leemaskMod`` with that database yields slight worse results.)
postprocessing (str, Optional): Select between ``HE`` (histogram
equalization, as with :py:func:`bob.ip.base.histogram_equalization`),
......
.. vim: set fileencoding=utf-8 :
.. Mon 11 Jul 2016 16:35:18 CEST
.. _experiments:
=====================
Running Experiments
=====================
For running experiments with a defined setup, you should use ``bin/verify.py``
directly. Follow the instructions on bob.bio.base_ for listing and using all
resources available in this package. In this section, we discuss specificities
for added plugins.
.. _databases:
Databases
---------
Required Parameters
~~~~~~~~~~~~~~~~~~~
* ``name``: The name of the database, in lowercase letters without special
characters. This name will be used as a default sub-directory to separate
resulting files of different experiments.
* ``protocol``: The name of the protocol that should be used. If omitted, the
protocol ``Default`` will be used (which might not be available in all
databases, so please specify).
.. _preprocessors:
Preprocessors
-------------
Vein Cropping Parameters
~~~~~~~~~~~~~~~~~~~~~~~~
* ``mask_h``: Height of the cropping finger mask.
* ``mask_w``: Width of the cropping finger mask.
* ``padding_offset``: An offset to the paddy array to be applied arround the
fingervein image.
* ``padding_threshold``: The pixel value of this paddy array. Defined to 0.2 to
uncontrolled (low quality) fingervein databases and to 0 for controlled (high
quality) fingervein databases. (By default 0.2).
* ``preprocessing``: The pre-processing applied to the fingervein image before
finger contour extraction. By default equal to ``None``.
* ``fingercontour``: The algorithm used to localize the finger contour.
Options: 'leemaskMatlab' - Implementation based on [LLP09]_, 'leemaskMod' -
Modification based on [LLP09]_ for uncontrolled images introduced by author,
and 'konomask' - Implementation based on [KUU02]_.
* ``postprocessing``: The post-processing applied to the fingervein image after
the finger contour extraction. Options: 'None', 'HE' - Histogram
Equalization, 'HFE' - High Frequency Enphasis Filtering [ZTXL09]_,
'CircGabor' - Circular Gabor Filters [ZY09]_.
.. note::
Currently, the pre-processing is fixed to ``None`` by default.
.. _algorithms:
Recognition Algorithms
----------------------
There are also a variety of recognition algorithms implemented in the
FingerveinRecLib. All finger recognition algorithms are based on the
:py:class:`FingerveinRecLib.tools.Tool` base class. This base class has
parameters that some of the algorithms listed below share. These parameters
mainly deal with how to compute a single score when more than one feature is
provided for the model or for the probe:
Here is a list of the most important algorithms and their parameters:
* :py:class:`FingerveinRecLib.tools.MiuraMatch`: Computes the match ratio based
on [MNM04]_ convolving the two template image. Return score - Value between
0 and 0.5, larger value is better match.
* ``ch``: Maximum search displacement in y-direction. Different defult values
based on the different features.
* ``cw``: Maximum search displacement in x-direction. Different defult values
based on the different features.
* :py:class:`FingerveinRecLib.tools.HammingDistance`: Computes the Hamming Distance between two fingervein templates.
.. include:: links.rst
Markdown is supported
0%
or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment