@TechReport{Spacek-CAK-2009-33,
  IS = { zkontrolovano 25 Jan 2010 },
  UPDATE  = { 2009-07-27 },
 author =        {Spacek, Libor},
 title =         {Libor's Vision Library (Version 1.9 Manual)},
 institution =   {Department of Cybernetics, Faculty of Electrical Engineering,
                  Czech Technical University},
 address =       {Prague, Czech Republic},
 year =          {2009},
 month =         {May},
 type =          {Research Report},
 number =        {K333--33/09, CTU--CMP--2009--08},
 pages =         {29},
 figures =       {6},
 authorship =    {100},
 psurl =         {[Spacek-TR-2009-08.pdf]},
 www =           {http://code.google.com/p/vision-lib, /datagrid/ViSOR/cmp/lvl/linux64-binaries/doc/lvl.pdf},
 project =       {1M0567},
 issn =          {1213-2365},
 annote = {The aims of the LVL project are: (a) to design an
   extensible common framework for computer vision programming, (b) to
   provide a software library based on such design and (c) to make
   available some useful tools using the library. The objectives are:
   simplicity, ortability, and accurate results. The library provides
   functions for automatic reading and writing of disk files in a
   number of general formats, suitable for most computer vision
   purposes. Several formats are predefined and many new file formats
   can be easily defined and used. Internally, LVL can convert various
   intermediate results to floating point numbers. These are used to
   prevent information loss arising from quantising certain computed
   pixel values or coordinates. The internal floating point format
   also facilitates normalisation of heterogeneous data to the
   standard range [0,1] and thus allows consistent application of
   thresholds and other computational benefits. The library includes a
   number of image processing functions which operate on single sample
   (8bit pixel) grayscale images (bw), on three samples, such as
   standard 24bit red-green-blue images (rgb), and on general n
   samples images. Various utilities are provided for explicit
   conversions and samples reductions. Most LVL image processing
   functions automatically recognise these types of images and apply
   appropriate methods. The library has functions implementing novel
   methods for finding edgepoints (edgels) and their contrast and also
   for thinning edgels. Graphics facilities and graphical user
   interfaces (guis) are omitted in the interest of portability but it
   is easy to use external utilities.},
 keywords =      {Vision,library,C,general image format,edge finding},
 comment =       {LVL manual as per my seminar of 21.5.2009},
}