opencv/samples/cpp/logpolar_bsm.cpp
2013-04-16 12:00:02 +04:00

85 lines
2.2 KiB
C++

/*Authors
* Manuela Chessa, Fabio Solari, Fabio Tatti, Silvio P. Sabatini
*
* manuela.chessa@unige.it, fabio.solari@unige.it
*
* PSPC-lab - University of Genoa
*/
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <cmath>
using namespace cv;
using namespace std;
static void help()
{
cout << "LogPolar Blind Spot Model sample.\nShortcuts:"
"\n\tn for nearest pixel technique"
"\n\tb for bilinear interpolation technique"
"\n\to for overlapping circular receptive fields"
"\n\ta for adjacent receptive fields"
"\n\tq or ESC quit\n";
}
int main(int argc, char** argv)
{
Mat img = imread(argc > 1 ? argv[1] : "lena.jpg",1); // open the image
if(img.empty()) // check if we succeeded
{
cout << "can not load image\n";
return 0;
}
help();
Size s=img.size();
int w=s.width, h=s.height;
int ro0=3; //radius of the blind spot
int R=120; //number of rings
//Creation of the four different objects that implement the four log-polar transformations
//Off-line computation
Point2i center(w/2,h/2);
LogPolar_Interp nearest(w, h, center, R, ro0, INTER_NEAREST);
LogPolar_Interp bilin(w,h, center,R,ro0);
LogPolar_Overlapping overlap(w,h,center,R,ro0);
LogPolar_Adjacent adj(w,h,center,R,ro0,0.25);
namedWindow("Cartesian",1);
namedWindow("retinal",1);
namedWindow("cortical",1);
int wk='n';
Mat Cortical, Retinal;
//On-line computation
for(;;)
{
if(wk=='n'){
Cortical=nearest.to_cortical(img);
Retinal=nearest.to_cartesian(Cortical);
}else if (wk=='b'){
Cortical=bilin.to_cortical(img);
Retinal=bilin.to_cartesian(Cortical);
}else if (wk=='o'){
Cortical=overlap.to_cortical(img);
Retinal=overlap.to_cartesian(Cortical);
}else if (wk=='a'){
Cortical=adj.to_cortical(img);
Retinal=adj.to_cartesian(Cortical);
}
imshow("Cartesian", img);
imshow("cortical", Cortical);
imshow("retinal", Retinal);
int c=waitKey(15);
if (c>0) wk=c;
if(wk =='q' || (wk & 255) == 27) break;
}
return 0;
}