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git-subtree-dir: external/CImg git-subtree-split: c0becdf881b0f3e2445975cac01c2422170d1fd9
120 lines
4.8 KiB
C++
120 lines
4.8 KiB
C++
/*
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#
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# File : use_skeleton.cpp
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# ( C++ source file )
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#
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# Description : Example of use for the CImg plugin 'plugins/skeleton.h'.
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# This file is a part of the CImg Library project.
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# ( http://cimg.eu )
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#
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# Copyright : Francois-Xavier Dupe
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# ( http://www.greyc.ensicaen.fr/~fdupe/ )
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#
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# License : CeCILL v2.0
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# ( http://www.cecill.info/licences/Licence_CeCILL_V2-en.html )
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#
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# This software is governed by the CeCILL license under French law and
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# abiding by the rules of distribution of free software. You can use,
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# modify and/ or redistribute the software under the terms of the CeCILL
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# license as circulated by CEA, CNRS and INRIA at the following URL
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# "http://www.cecill.info".
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#
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# As a counterpart to the access to the source code and rights to copy,
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# modify and redistribute granted by the license, users are provided only
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# with a limited warranty and the software's author, the holder of the
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# economic rights, and the successive licensors have only limited
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# liability.
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#
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# In this respect, the user's attention is drawn to the risks associated
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# with loading, using, modifying and/or developing or reproducing the
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# software by the user in light of its specific status of free software,
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# that may mean that it is complicated to manipulate, and that also
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# therefore means that it is reserved for developers and experienced
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# professionals having in-depth computer knowledge. Users are therefore
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# encouraged to load and test the software's suitability as regards their
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# requirements in conditions enabling the security of their systems and/or
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# data to be ensured and, more generally, to use and operate it in the
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# same conditions as regards security.
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#
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# The fact that you are presently reading this means that you have had
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# knowledge of the CeCILL license and that you accept its terms.
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#
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*/
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#include <queue>
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#define cimg_plugin "plugins/skeleton.h"
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#include "CImg.h"
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using namespace cimg_library;
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#ifndef cimg_imagepath
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#define cimg_imagepath "img/"
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#endif
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// Main procedure
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//----------------
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int main (int argc, char **argv) {
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cimg_usage("Compute the skeleton of a shape, using Hamilton-Jacobi equations");
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// Read command line arguments
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cimg_help("Input/Output options\n"
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"--------------------");
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const char* file_i = cimg_option("-i",cimg_imagepath "milla.bmp","Input (black&white) image");
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const int median = cimg_option("-median",0,"Apply median filter");
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const bool invert = cimg_option("-inv",false,"Invert image values");
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const char* file_o = cimg_option("-o",(char*)0,"Output skeleton image");
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const bool display = cimg_option("-visu",true,"Display results");
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cimg_help("Skeleton computation parameters\n"
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"-------------------------------");
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const float thresh = cimg_option("-t",-0.3f,"Threshold");
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const bool curve = cimg_option("-curve",false,"Create medial curve");
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cimg_help("Torsello correction parameters\n"
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"------------------------------");
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const bool correction = cimg_option("-corr",false,"Torsello correction");
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const float dlt1 = 2;
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const float dlt2 = cimg_option("-dlt",1.0f,"Discrete step");
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// Load the image (forcing it to be scalar with 2 values { 0,1 }).
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CImg<unsigned int> image0(file_i), image = image0.get_norm().quantize(2).normalize(0.0f,1.0f).round();
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if (median) image.blur_median(median);
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if (invert) (image-=1)*=-1;
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if (display) (image0.get_normalize(0,255),image.get_normalize(0,255)).display("Input image - Binary image");
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// Compute distance map.
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CImgList<float> visu;
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CImg<float> distance = image.get_distance(0);
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if (display) visu.insert(distance);
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// Compute the gradient of the distance function, and the flux (divergence) of the gradient field.
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const CImgList<float> grad = distance.get_gradient("xyz");
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CImg<float> flux = image.get_flux(grad,1,1);
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if (display) visu.insert(flux);
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// Use the Torsello correction of the flux if necessary.
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if (correction) {
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CImg<float>
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logdensity = image.get_logdensity(distance,grad,flux,dlt1),
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nflux = image.get_corrected_flux(logdensity,grad,flux,dlt2);
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if (display) visu.insert(logdensity).insert(nflux);
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flux = nflux;
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}
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if (visu) {
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cimglist_apply(visu,normalize)(0,255);
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visu.display(visu.size()==2?"Distance function - Flux":"Distance function - Flux - Log-density - Corrected flux");
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}
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// Compute the skeleton
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const CImg<unsigned int> skel = image.get_skeleton(flux,distance,curve,thresh);
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if (display) {
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(image0.resize(-100,-100,1,3)*=0.7f).get_shared_channel(1)|=skel*255.0;
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image0.draw_image(0,0,0,0,image*255.0,0.5f).display("Image + Skeleton");
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}
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// Save output image if necessary.
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if (file_o) skel.save(file_o);
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return 0;
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}
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