/*
#
# File : use_skeleton.cpp
# ( C++ source file )
#
# Description : Example of use for the CImg plugin 'plugins/skeleton.h'.
# This file is a part of the CImg Library project.
# ( http://cimg.sourceforge.net )
#
# Copyright : Francois-Xavier Dupe
# ( http://www.greyc.ensicaen.fr/~fdupe/ )
#
# License : CeCILL v2.0
# ( http://www.cecill.info/licences/Licence_CeCILL_V2-en.html )
#
# This software is governed by the CeCILL license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/ or redistribute the software under the terms of the CeCILL
# license as circulated by CEA, CNRS and INRIA at the following URL
# "http://www.cecill.info".
#
# As a counterpart to the access to the source code and rights to copy,
# modify and redistribute granted by the license, users are provided only
# with a limited warranty and the software's author, the holder of the
# economic rights, and the successive licensors have only limited
# liability.
#
# In this respect, the user's attention is drawn to the risks associated
# with loading, using, modifying and/or developing or reproducing the
# software by the user in light of its specific status of free software,
# that may mean that it is complicated to manipulate, and that also
# therefore means that it is reserved for developers and experienced
# professionals having in-depth computer knowledge. Users are therefore
# encouraged to load and test the software's suitability as regards their
# requirements in conditions enabling the security of their systems and/or
# data to be ensured and, more generally, to use and operate it in the
# same conditions as regards security.
#
# The fact that you are presently reading this means that you have had
# knowledge of the CeCILL license and that you accept its terms.
#
*/
#include <queue>
#define cimg_plugin "plugins/skeleton.h"
#include "CImg.h"
using namespace cimg_library;
#ifndef cimg_imagepath
#define cimg_imagepath "img/"
#endif
// Main procedure
//----------------
int main (int argc, char **argv) {
cimg_usage("Compute the skeleton of a shape, using Hamilton-Jacobi equations");
// Read command line arguments
cimg_help("Input/Output options\n"
"--------------------");
const char* file_i = cimg_option("-i",cimg_imagepath "milla.bmp","Input (black&white) image");
const int median = cimg_option("-median",0,"Apply median filter");
const bool invert = cimg_option("-inv",false,"Invert image values");
const char* file_o = cimg_option("-o",(char*)0,"Output skeleton image");
const bool display = cimg_option("-visu",true,"Display results");
cimg_help("Skeleton computation parameters\n"
"-------------------------------");
const float thresh = cimg_option("-t",-0.3f,"Threshold");
const bool curve = cimg_option("-curve",false,"Create medial curve");
cimg_help("Torsello correction parameters\n"
"------------------------------");
const bool correction = cimg_option("-corr",false,"Torsello correction");
const float dlt1 = 2;
const float dlt2 = cimg_option("-dlt",1.0f,"Discrete step");
// Load the image (forcing it to be scalar with 2 values { 0,1 }).
CImg<unsigned int> image0(file_i), image = image0.get_norm().quantize(2).normalize(0.0f,1.0f);
if (median) image.blur_median(median);
if (invert) (image-=1)*=-1;
if (display) (image0.get_normalize(0,255),image.get_normalize(0,255)).display("Input image - Binary image");
// Compute distance map.
CImgList<float> visu;
CImg<float> distance = image.get_distance(0);
if (display) visu.insert(distance);
// Compute the gradient of the distance function, and the flux (divergence) of the gradient field.
const CImgList<float> grad = distance.get_gradient("xyz");
CImg<float> flux = image.get_flux(grad,1,1);
if (display) visu.insert(flux);
// Use the Torsello correction of the flux if necessary.
if (correction) {
CImg<float>
logdensity = image.get_logdensity(distance,grad,flux,dlt1),
nflux = image.get_corrected_flux(logdensity,grad,flux,dlt2);
if (display) visu.insert(logdensity).insert(nflux);
flux = nflux;
}
if (visu) {
cimglist_apply(visu,normalize)(0,255);
visu.display(visu.size()==2?"Distance function - Flux":"Distance function - Flux - Log-density - Corrected flux");
}
// Compute the skeleton
const CImg<unsigned int> skel = image.get_skeleton(flux,distance,curve,thresh);
if (display) {
(image0.resize(-100,-100,1,3)*=0.7f).get_shared_channel(1)|=skel*255.0;
image0.draw_image(0,0,0,0,image*255.0,0.5f).display("Image + Skeleton");
}
// Save output image if necessary.
if (file_o) skel.save(file_o);
return 0;
}