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#include <stdlib.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
using namespace cv;
/*************************************** FONCTION SOBEL + THRESHOLD ************************************************/
int main( )
{
int height,width,step,step_mono,channels; /*Here i have declared step_mono for handling the widthstep member of a monochrome image*/
uchar *data,*data_mono; /*similarly data mono for handling the data of monochrome image*/
int i,j,k;
//Mat src;
Mat src_gray;
Mat grad;
char* window_name = "Sobel Demo - Simple Edge Detector";
int scale = 1;
int delta = 0;
int ddepth = CV_16S;
int c;
/// Load an image
IplImage* frame=cvLoadImage("D:/Entwicklung/OpenCV/2010/Kopie von assemblage sobel + threshold/Release/image sans contre jour.bmp",1);
if( frame == NULL )
{ return -1; }
Mat src(frame);
GaussianBlur(src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
/// Convert it to gray
cvtColor( src, src_gray, CV_RGB2GRAY );
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
/// Generate grad_x and grad_y
Mat grad_x, grad_y;
Mat abs_grad_x, abs_grad_y;
/// Gradient X
//Scharr( src_gray, grad_x, ddepth, 1, 0, scale, delta, BORDER_DEFAULT );
Sobel( src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT );
convertScaleAbs( grad_x, abs_grad_x );
/// Gradient Y
//Scharr( src_gray, grad_y, ddepth, 0, 1, scale, delta, BORDER_DEFAULT );
Sobel( src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT );
convertScaleAbs( grad_y, abs_grad_y );
/// Total Gradient (approximate)
addWeighted( abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad );
imshow( window_name, grad );
//Resultat de grad dans IPL ....
//IplImage mono_thres=cvCreateImage( cvGetSize(frame), 8, 1 );
IplImage frame2(grad);
//Faire à la fin
IplImage* mono_thres=cvCreateImage( cvGetSize(&frame2), 8, 1 );
height = frame2.height; /*height is a member of IPLIMAGE structure and hence it comes handy like this in such situations, and same goes with below four statements*/
width = frame2.width;
step = frame2.widthStep;
step_mono = mono_thres->widthStep;
channels = frame2.nChannels; /*Number of channels in the image*/
data = (uchar *)frame2.imageData; /*Image is treated as as unsigned char data hence we use an unsigned char pointer to point to the same*/
cvNamedWindow("My Window", CV_WINDOW_AUTOSIZE );
data_mono = (uchar *)mono_thres-> imageData; /*data of mono image is handled by the data_mono*/
for(i=0;i < height;i++) for(j=0;j < width;j++) /*I am copying the first channel from the image in "frame" in the monochrome image with the help of this line below..*/
data_mono[i*step_mono+j*1+0]=data[i*step+j*channels+0];
//cvThreshold(mono_thres,mono_thres,12, /*70 is the lower cut off*/
//40, /*this is the higher cut off*/
//CV_THRESH_BINARY /*The type of thresholding,more description in the documentation*/
cvThreshold(mono_thres,mono_thres,60, /*70 is the lower cut off*/
140, /*this is the higher cut off*/
CV_THRESH_BINARY /*The type of thresholding,more description in the documentation*/
);
//imshow( window_name, grad );
cvShowImage("My Window",mono_thres);
waitKey(0);
//cvDestroyWindow( "My Window" );
/**************************************************** HOUGH Fonction ***************************************************/
//Mat gray;
/*if( argc != 2 && !(img=imread(argv[1], 1)).data)
return -1;*/
Mat gray(mono_thres);
Mat img(mono_thres);
//cvtColor(img, gray, CV_BGR2GRAY);
// smooth it, otherwise a lot of false circles may be detected
//GaussianBlur( gray, gray, Size(9, 9), 2, 2 );
vector<Vec3f> circles;
HoughCircles(gray, circles, CV_HOUGH_GRADIENT,
2, gray.rows/4, 200, 100 );
for( size_t i = 0; i < circles.size(); i++ )
{
Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
int radius = cvRound(circles[i][2]);
// draw the circle center
circle( img, center, 3, Scalar(255,0,0), -1, 8, 0 );
// draw the circle outline
circle( img, center, radius, Scalar(255,0,0), 3, 8, 0 );
}
namedWindow( "circles", 1 );
imshow( "circles", img );
waitKey(0);
return 0;
} |
