CV Hough Circle Parameters to detect Circles

Question

I am trying to detect 22 balls on the snooker table. I have an image to test on but programme os detecting 2 balls, and random circles elsewhere. My code is below with the circle detection algorithm. Does anyone know which parameters should be adjusted to get the detection i would need? thanks

#include <cv.h>
#include <highgui.h>
#include <math.h>

int main(int argc, char** argv)
{   int edge_thresh = 1;
    IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png", 1);;
    IplImage* gray = cvCreateImage(cvGetSize(img), 8, 1);
     IplImage *edge = cvCreateImage( cvSize(img->width,img->height), 8, 1);
    CvMemStorage* storage = cvCreateMemStorage(0);
    cvCvtColor(img, gray, CV_BGR2GRAY);
    cvThreshold(gray,gray, CV_GAUSSIAN, 9, 9);
    cvSmooth(gray, gray, CV_GAUSSIAN, 11, 11); 
    cvCanny(gray, edge, (float)edge_thresh, (float)edge_thresh*3, 5);
    CvSeq* circles = cvHoughCircles(edge, storage, 
        CV_HOUGH_GRADIENT, 2, 20, 200, 50);
    int i;

    for (i = 0; i < circles->total; i++) 
    {
         float* p = (float*)cvGetSeqElem( circles, i );
         cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])), 
             3, CV_RGB(0,255,0), -1, 8, 0 );
         cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])), 
             cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
    }
    cvNamedWindow( "circles", 1 );
    cvShowImage( "circles", img );


    return 0;
}

Answer 1

I suspect you are having trouble with the parameters being either too restrictive or loose. You need to play with the parameters until you get the number of circles you want. Also, the Gaussian 11x11 blur may be a bit aggressive depending on the image. For my image, it was doing more harm than good, but my image is kind of idealized...

I modified the OpenCV example you are using to include the track bars allowing you to play with the Canny parameters. This should really help you get a feel for how it works. Also, pay attention to the minDist parameter. For my image, the circle centers were about 32 pixels away. You'll need to adjust this to your circle sizes. So, here is the sample:

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

using namespace cv;

int hi = 1, lo = 1;

int main(int argc, char* argv[]) {
    Mat orig = imread("Snooker_balls_triangled.png");
    int key = 0;

    namedWindow("circles", 1);
    createTrackbar("hi", "circles", &hi, 255);
    createTrackbar("lo", "circles", &lo, 255);

    do
    {
        // update display and snooker, so we can play with them
        Mat display = orig.clone();

        Mat snooker;
        cvtColor(orig, snooker, CV_RGB2GRAY);

        vector<Vec3f> circles;

        // also preventing crash with hi, lo threshold here...
        HoughCircles(snooker, circles, CV_HOUGH_GRADIENT, 2, 32.0, hi > 0 ? hi : 1, lo > 0 ? lo : 1 );
        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 green circle center
             circle( display, center, 3, Scalar(0,255,0), -1, 8, 0 );

             // draw the blue circle outline
             circle( display, center, radius, Scalar(255,0,0), 3, 8, 0 );
        }

        imshow( "circles", display );
        imshow("snooker", snooker);
        key = waitKey(33);
    } while((char)key != 27);
    return 0;
}

I used this snooker image, and this is the output I get.

(P.S. consider using the C++ interface it's far superior to the C interface IMHO :)

Answer 2

If you are using iOS you need to include the ios.h, or simply write your own class methods to handle the img proc from cvMat to UIImage and vice versa.

Please excuse the comments, I included them only for those that maybe have uncover some of the same 'gibberish' research as me. Every image will require totally different settings. Do not give up. houghcircles is about the best detection algorithm out there. I am about to combine some gaming code with detection to make it better, simpler, faster.

    #import "JmBViewController.h"

@interface JmBViewController ()

@end

@implementation JmBViewController

- (void)viewDidLoad {
[super viewDidLoad];
_imgtest = [UIImage imageNamed:@"IMG_0424.PNG"];

cv::Mat cvImage;
UIImageToMat(_imgtest, cvImage);
if (!cvImage.empty()) {
    cv::Mat gray;
  //  cv::Mat filteredMat;
    cv::cvtColor(cvImage, gray, CV_BGRA2GRAY);
   // cv::GaussianBlur(gray, gray, cv::Size(5, 5), 1.2, 1.2);
    cv::vector<cv::Vec3f> circles;
    //cv::HoughCircles(gray, circles, CV_HOUGH_GRADIENT, 1, 50);
    /*
    for(size_t i = 0; i < circles.size(); i++)
    {
        cv::Point center((cvRound(circles[i][0]), cvRound(circles[i][1])));
        int radius = cvRound(circles[i][2]);
        cv::circle(gray, center, 3, cv::Scalar(0,255,0));
        cv::circle(gray, center, radius, cv::Scalar(0,0,255));
    }
   */

 //  for ( int i = 1; i < 15; i = i + 2 )

        cv::GaussianBlur(gray, gray, cv::Size(9, 9), 1.5, 1.5);

        cv::Mat edges;
        cv::Canny(gray, edges, 0, 50);
        //gray.setTo(cv::Scalar::all(0));
        //gray.setTo(cv::Scalar::all(255), edges);
        cv::HoughCircles(gray, circles, CV_HOUGH_GRADIENT, 1, gray.rows/30, 100, 50, 10, 30 );
        for(size_t i = 0; i < circles.size(); i++)
        {
            cv::Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
            int radius = cvRound(circles[i][2]);
            cv::circle(cvImage, center, 5, cv::Scalar::all(200), -1, 8, 0 );//center
            cv::circle(cvImage, center, radius, cv::Scalar::all(255), 3, 8, 0 );//diamter
        NSLog(@"Circles: %ld", i+1);

       // cv::imshow(&"circles i " [ i], gray);
    }


    _imgView.image = MatToUIImage(cvImage);
    }
    /*
cv::Mat cvImage;
cv::Mat grey;
cv::Mat filteredMat;
cv::vector<cv::Vec3f> circles;
// cv::cvtColor(_imgtest, cvImage, CV_BGR2GRAY);
cv::threshold(grey, filteredMat, 100, 255, CV_THRESH_BINARY);
[UIImageCVMatConverter cvMatGrayFromUIImage:_imgtest];
//  cv::cvtColor(cvImage, grey, CV_RGBA2GRAY);
// UIImageToMat(_imgtest, cvImage);
cv::HoughCircles(cvImage, circles, CV_HOUGH_GRADIENT, 1, 50);
//  MatToUIImage(cvImage);
_imgView.image = [UIImageCVMatConverter UIImageFromCVMat:cvImage];
_imgView.image = MatToUIImage(cvImage);
*/

// Do any additional setup after loading the view, typically from a nib.
}

- (void)didReceiveMemoryWarning
{
[super didReceiveMemoryWarning];
// Dispose of any resources that can be recreated.
}
/*

UIImage* MatToUIImage(const cv::Mat& image) {
NSData *data = [NSData dataWithBytes:image.data length:image.elemSize()*image.total()];
CGColorSpaceRef colorSpace;
if (image.elemSize() == 1) {
    colorSpace = CGColorSpaceCreateDeviceGray();
}else { colorSpace = CGColorSpaceCreateDeviceRGB();
 }
CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);

CGImageRef imageRef = CGImageCreate(image.cols, image.rows, 8, 8*image.elemSize(), image.step.p[0], colorSpace, kCGImageAlphaNone|kCGBitmapByteOrderDefault, provider, NULL, FALSE, kCGRenderingIntentDefault);
UIImage *finalImage = [UIImage imageWithCGImage:imageRef];

return finalImage;
 }
 */


@end