updated documentation

doc/evaluate.rst

@@ -32,7 +32,6 @@ Evaluation
 ----------
 Since all required information is available in the score file, you can use any tool (like MatLab) to evaluate the score file and compute error measures or generate plots.
 The FingerveinRecLib defines one generic script that is able to evaluate the score files, compute some error measures and generate various types of plots.
-For example, the plots shown in section :ref:`baseline_results` are generated with this script.
 This script is called ``bin/evaluate.py`` and has the following command line options (see ``bin/evaluate.py --help`` for the shortcuts):
 
 * ``--dev-files``: A list of files of the development set that will be evaluated.

doc/experiments.rst

@@ -138,16 +138,16 @@ Fingervein Cropping Parameters
 
 * ``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).
+  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'.
+  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]_.
+  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]_.
+  Options:  'None', 'HE' - Histogram Equalization, 'HFE' - High Frequency Enphasis Filtering [ZTXL09]_, 'CircGabor' - Circular Gabor Filters [ZY09]_.
 
 
 Preprocessor Classes
@@ -190,7 +190,7 @@ 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.
+  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.

doc/index.rst

@@ -4,9 +4,9 @@
 
 .. _fingerveinreclib:
 
-============================================
+=============================================
  Welcome to FingerveinRecLib's documentation!
-============================================
+=============================================
 
 The FingerveinRecLib is an open source tool (based on FaceRecLib_) that is designed to run comparable and reproducible fingervein recognition experiments.
    Most of this documentation is based on the documentation of FaceRecLib_.
@@ -38,7 +38,6 @@ Users Guide
    installation
    experiments
    evaluate
-   
    contribute
    satellite
    references
@@ -48,5 +47,4 @@ This documentation is still under development.
 
 
 .. include:: links.rst
-
 .. _facereclib: http://pythonhosted.org/facereclib/index.html
\ No newline at end of file

doc/links.rst

@@ -9,13 +9,11 @@
 .. _bob: http://www.idiap.ch/software/bob
 .. _github bug reporting system: http://github.com/bioidiap/fingervein/issues
 .. _idiap at github: http://www.github.com/bioidiap
-.. _at&t database: http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html
 .. _bob's github page: http://idiap.github.com/bob
 .. _gridtk: http://github.com/idiap/gridtk
 .. _buildout: http://www.buildout.org
 .. _nist: http://www.nist.gov/itl/iad/ig/focs.cfm
 .. _pypi: http://pypi.python.org
 .. _sge: http://wiki.idiap.ch/linux/SunGridEngine
-.. _xfacereclib.extension.csu: http://pypi.python.org/pypi/xfacereclib.extension.CSU
 .. _virtualbox: https://www.virtualbox.org
 .. _hdf5: http://www.hdfgroup.org/HDF5

doc/references.rst

@@ -7,6 +7,7 @@ References
 ==========
 
 .. [LLP09]_  *E.C. Lee, H.C. Lee and K.R. Park. Finger vein recognition using minutia-based alignment and local binary pattern-based feature extraction. International Journal of Imaging Systems and Technology. Vol. 19, No. 3, pp. 175-178, September 2009.
+
 .. [KUU02]_  *M. Kono, H. Ueki and S. Umemura. Near-infrared finger vein patterns for personal identification, Applied Optics, Vol. 41, Issue 35, pp. 7429-7436 (2002).
 
 .. [ZY09]_   *J. Zhang and J. Yang. Finger-vein image enhancement based on combination of gray-level grouping and circular gabor filter. In International Conference on Information Engineering and Computer Science (ICIECS), pp. 1-4, Dec 2009.
@@ -20,4 +21,3 @@ References
 .. [HDLTL10]_  *B. Huang, Y. Dai, R. Li, D. Tang and W. Li. Finger-vein authentication based on wide line detector and pattern normalization, Proceedings on 20th International Conference on Pattern Recognition (ICPR), 2010.
 
 .. [MD13]_  *L. Mirmohamadsadeghi and A. Drygajlo. Palm vein recognition uisng local texture patterns, IET Biometrics, pp. 1-9, 2013.
-