霍夫变换检测圆c 语言,c – 使用Hough变换检测圆

我正在尝试使用霍夫变换来检测圆圈.

使用我当前的代码,我可以检测到下面的代码

但我想在我发现的圆圈内找到黑洞.

然而,改变houghcircle方法的参数对我没有帮助.实际上它找到了不存在的圆圈.

此外,我已经尝试裁剪我发现的圆圈,并在这个新的部分做另一个hough变换它也没有帮助我.

这是我的代码

#include

#include

#include "opencv2/core/core.hpp"

#include "opencv2/features2d/features2d.hpp"

#include "opencv2/highgui/highgui.hpp"

#include "opencv2/calib3d/calib3d.hpp"

#include "opencv2/nonfree/nonfree.hpp"

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/opencv.hpp" // needs imgproc, imgcodecs & highgui

using namespace cv;

using namespace std;

int main(int argc, char** argv)

{

Mat src, circleroi;

/// Read the image

src = imread( "/Users/Rodrane/Documents/XCODE/test/mkedenemeleri/alev/delikli/gainfull.jpg", 2 );

/// Convert it to gray

// cvtColor( src, src_gray, CV_BGR2GRAY );

/// Reduce the noise so we avoid false circle detection

GaussianBlur( src, src, Size(3, 3), 2, 2 );

// adaptiveThreshold(src,src,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,9,14);

vector circles,circlessmall;

// Canny( src, src, 50 , 70, 3 );

/// Apply the Hough Transform to find the circles

HoughCircles( src, circles, CV_HOUGH_GRADIENT, 1, src.rows/8, 200, 100, 0, 0 );

/// Draw the circles detected

for( size_t i = 0; i < circles.size(); i++ )

{

Point center(cvRound(circles[i][0]), cvRound(circles[i][4]));

int radius = cvRound(circles[i][5]);

// circle center

circle( src, center, 3, Scalar(0,255,0), -1, 8, 0 );

// circle outline

circle( src, center, radius, Scalar(0,255,0), 3, 8, 0 );

circleroi = src(Rect(center.x - radius, // ROI x-offset, left coordinate

center.y - radius, // ROI y-offset, top coordinate

2*radius, // ROI width

2*radius));

// imshow( "Hough Circle Transform Demo", circleroi );

}

resize(src, src, Size(src.cols/2, src.rows/2));

// threshold( circleroi, circleroi, 50, 255,CV_THRESH_BINARY );

// cout<

imshow("asd",src);

// imwrite("/Users/Rodrane/Documents/XCODE/test/mkedenemeleri/alev/cikti/deliksiz.jpg",circleroi);

waitKey(0);

return 0;

}

更新：因为霍夫在内部使用canny我手动使用canny来看它是否找到了圆圈.

这里有精彩的结果

Canny(src,src,100,200,3);

谢谢