HoughCircle函数如何工作？我不能让它正常工作 [英] How does the HoughCircle function works? I can't get it to work properly

问题描述

我试图从摄像机中找到橙色球。

我将每个帧转换为HSV，将其模糊化，然后使用inRange过滤橙色颜色。然后我应用HoughCircles函数，但是找不到正确的参数。

当它工作时，它不是很稳定：圆不总是被检测到。 >

以下是屏幕截图以及设置代码：

截图

  #include< cv.h> 
 #include< highgui.h> 
 #include< stdio.h> 
 #include< vector> 
 
 using namespace cv; 
 
 int hmin [2] = {2,0}，smin [2] = {163,104}，vmin [2] = {16,29} 
 int hmax [2] = {16,25}，smax [2] = {255,255}，vmax [2] = {212,255}。 
 
 
 int p1 = 6，p2 = 12; 
 int f1 = 9，f2 = 3; 
 int main（）{
 VideoCapture cap（0）; 
 if（！cap.isOpened（））{
 fprintf（stderr，ERROR：capture is NULL \\\
）; 
 return -1; 
} 
 
 namedWindow（couleur，CV_WINDOW_AUTOSIZE）; 
 
 namedWindow（filtre1，CV_WINDOW_AUTOSIZE）; 
 createTrackbar（hmin [0]，filtre1，& hmin [0]，180，NULL）; 
 createTrackbar（smin [0]，filtre1，& smin [0]，255，NULL）; 
 createTrackbar（vmin [0]，filtre1，& vmin [0]，255，NULL）; 
 createTrackbar（hmax [0]，filtre1，& hmax [0]，180，NULL）; 
 createTrackbar（smax [0]，filtre1，& smax [0]，255，NULL）; 
 createTrackbar（vmax [0]，filtre1，& vmax [0]，255，NULL）; 
 
 namedWindow（hough，CV_WINDOW_AUTOSIZE）; 
 createTrackbar（p1，hough，& p1，500，NULL）; 
 createTrackbar（p2，hough，& p2，500，NULL）; 
 
 createTrackbar（f1，hough，& f1，30，NULL）; 
 createTrackbar（f2，hough，& f2，30，NULL）; 
 std :: vector< Vec3f>塞尔
 
 while（1）{
 Mat frame，hsv，orange; 
 cap>>帧; 
 
 f1 = f1％2 f1：f1 + 1; 
 
 cvtColor（frame，hsv，CV_BGR2HSV）; 
 GaussianBlur（hsv，hsv，Size（f1，f1），f2，f2）; 
 inRange（hsv，Scalar（hmin [0]，smin [0]，vmin [0]），Scalar（hmax [0]，smax [0]，vmax [0]）， 
 
 if（p1 <= 0）
 p1 = 1; 
 
 if（p2 <= 0）
 p2 = 1; 
 
 HoughCircles（orange，cercle，CV_HOUGH_GRADIENT，2，orange.rows / 4，p1，p2，0，30）; 
 
 for（uint i = 0; i  Point c（cvRound（cercle [i] [0]），cvRound（cercle [i ] [1]））; 
 int r = cvRound（cercle [i] [2]）; 
 circle（frame，c，3，Scalar（0,255,0），-1，8，0）; 
 circle（frame，c，r，Scalar（255,0,0），3，8，0）; 
 printf（％d）％d％d％d \\\
，i，c.x，c.y，r）; 
} 
 printf（--- \\\
）; 
 cercle.clear（）; 
 
 imshow（couleur，frame）; 
 imshow（filtre1，orange）; 
 
 if（（waitKey（10）& 255）== 27）break; 
} 
 return 0; 
} 
  

解决方案

。

param1（内部Canny边缘检测器的上限）在将图像传递到HoughCircles（）之前固定为100

将图像转换为灰度，并应用ksize 5的中间模糊。

虽然这适用于这一帧，我相信一系列视频帧将显示相当大的变化和不稳定性。例如，找到这张图片的设置，挑选这两个球，但不要选择框上的白色标签，这很难。

I'm trying to locate orange balls from a video camera.

I'm converting each frame to HSV, blurring it, and using inRange to filter the orange color. I then apply the HoughCircles function but I can't find the right parameters.

When it works, it's not very stable: the circle is not always detected.

Here is a screenshot plus the code of the setup:

screenshot

#include <cv.h> 
#include <highgui.h> 
#include <stdio.h>  
#include <vector>

using namespace cv;

int hmin[2] = {2,0}, smin[2] = {163,104}, vmin[2] = {16,29};
int hmax[2] = {16,25}, smax[2] = {255, 255}, vmax[2] = {212,255};


int p1 = 6, p2 = 12;
int f1 = 9, f2 = 3;
int main() {
     VideoCapture cap(0);
     if(!cap.isOpened()) {
          fprintf( stderr, "ERROR: capture is NULL \n" );
          return -1;
     }

     namedWindow( "couleur", CV_WINDOW_AUTOSIZE );

     namedWindow( "filtre1", CV_WINDOW_AUTOSIZE );
     createTrackbar("hmin[0]", "filtre1", &hmin[0], 180, NULL);
     createTrackbar("smin[0]", "filtre1", &smin[0], 255, NULL);
     createTrackbar("vmin[0]", "filtre1", &vmin[0], 255, NULL);
     createTrackbar("hmax[0]", "filtre1", &hmax[0], 180, NULL);
     createTrackbar("smax[0]", "filtre1", &smax[0], 255, NULL);
     createTrackbar("vmax[0]", "filtre1", &vmax[0], 255, NULL);

     namedWindow( "hough", CV_WINDOW_AUTOSIZE );
     createTrackbar("p1", "hough", &p1, 500, NULL);
     createTrackbar("p2", "hough", &p2, 500, NULL);

     createTrackbar("f1", "hough", &f1, 30, NULL);
     createTrackbar("f2", "hough", &f2, 30, NULL);
     std::vector<Vec3f> cercle;

     while ( 1 ) {
          Mat frame, hsv, orange;
          cap >> frame;

          f1 = f1%2?f1:f1+1;

          cvtColor(frame, hsv, CV_BGR2HSV);
          GaussianBlur(hsv, hsv, Size(f1, f1), f2, f2 );
          inRange(hsv, Scalar(hmin[0],smin[0],vmin[0]), Scalar(hmax[0],smax[0],vmax[0]), orange);

          if(p1 <= 0)
               p1 = 1;

          if(p2 <= 0)
               p2 = 1;

          HoughCircles(orange, cercle, CV_HOUGH_GRADIENT, 2, orange.rows/4, p1, p2, 0, 30);

          for(uint i = 0; i < cercle.size(); i++) {
               Point c(cvRound(cercle[i][0]), cvRound(cercle[i][1]));
               int r = cvRound(cercle[i][2]);
               circle(frame, c, 3, Scalar(0,255,0), -1, 8, 0);
               circle(frame, c, r, Scalar(255,0,0), 3, 8, 0);
               printf("%d) %d %d %d\n", i, c.x, c.y, r);
          }
          printf("---\n");
          cercle.clear();

          imshow("couleur", frame );
          imshow("filtre1", orange );

          if ( (waitKey(10) & 255) == 27 ) break;
     }
     return 0;
}

解决方案

Here are some parameters that work.

param1 (upper threshold for the internal Canny edge detector) is fixed at 100

before passing image in to HoughCircles() the image is converted to grayscale and a median blur of ksize 5 is applied.

Although this works for this one still frame, I am sure that a series of video frames will show a fair amount of variation and instability. For example, it's quite tricky to find settings for this image that pick out both of the balls but don't also select the white labels on the boxes.

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