voronoi

The morphological skeleton of an image is the set of its non-zero pixels which are equidistant to its boundaries. More info on Wikipedia.

Thinning an image consits in reducing its non-zero pixels to their morphological skeleton. More info on Wikipedia.

VoronoiSkeleton is a C++ class made for the fast computing of Voronoi diagrams of monochrome images. It contains different implementations of thinning algorithms:

• Zhang - Suen explained in 'A fast parallel algorithm for thinning digital patterns' by T.Y. Zhang and C.Y. Suen and based on this implentation

• Guo - Hall explained in 'Parallel thinning with two sub-iteration algorithms' by Zicheng Guo and Richard Hall and based on this implentation

• a morphological one, based on the erode() and dilate() operators. Coming from previous work by Félix Abecassis.

A special care has been given to optimize the 2 first ones. Instead of re-examining the whole image at each iteration, only the pixels of the current contour are considered. This leads to a speedup by almost 100 times on experimental tests.

Licence

LGPL v3, check file LICENCE.

Dependencies

You need the following libraries before compiling :

• cmake ( $ sudo apt-get install cmake ),
• GTest ( $ sudo apt-get install gtest-dev ),
• OpenCV ( $ sudo apt-get install libopencv-dev )

How to build the program

The project is based on a CMakeLists. It is easy to build the program on a Unix computer. Go in the source folder and type:

$ mkdir build
$ cd build
$ cmake ..
$ make

For Windows users, some instructions are available on OpenCV website: http://opencv.willowgarage.com/wiki/Getting_started .

How to use the program

To display the help, from the main folder, run the generated executable 'build/test_voronoi ' with no arguments. It will display the help of the program.

Related projects

mnist-digits-as-stroke-sequences Code project to transform the well known MNIST handwritten digit images to sequences of pen strokes, in order to obtain a data set for sequence learning.

Authors

Arnaud Ramey arnaud.a.ramey@gmail.com -- Robotics Lab, University Carlos III of Madrid