使用 OpenCV 对 HoughCircles 进行颜色检测

Question

我已经检测到 22 个球，并且正在努力寻找一种方法来对这些圆圈运行颜色检测算法以获取它们的颜色。我正在使用 HoughCircles 来检测圆圈，但不知道如何检查这些圆圈是什么颜色？ 源代码：

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

int main(int argc, char** argv)
{
    //load image from directory
    IplImage* img = cvLoadImage("C:\\Users\\Nathan\\Desktop\\SnookerPic.png");


    IplImage* gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
    CvMemStorage* storage = cvCreateMemStorage(0);

    //covert to grayscale
    cvCvtColor(img, gray, CV_BGR2GRAY);

    // This is done so as to prevent a lot of false circles from being detected
    cvSmooth(gray, gray, CV_GAUSSIAN, 7, 7);

    IplImage* canny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,1);
    IplImage* rgbcanny = cvCreateImage(cvGetSize(img),IPL_DEPTH_8U,3);
    cvCanny(gray, canny, 50, 100, 3);

    //detect circles
    CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 1, 35.0, 75, 60,0,0);
    cvCvtColor(canny, rgbcanny, CV_GRAY2BGR);

    //draw all detected circles
    for (int i = 0; i < circles->total; i++)
    {
         // round the floats to an int
         float* p = (float*)cvGetSeqElem(circles, i);
         cv::Point center(cvRound(p[0]), cvRound(p[1]));
         int radius = cvRound(p[2]);
         cvScalar c = cvGet2D(center.x, center.y);//colour of circle

         // draw the circle center
         cvCircle(img, center, 3, CV_RGB(0,255,0), -1, 8, 0 );

         // draw the circle outline
         cvCircle(img, center, radius+1, CV_RGB(0,0,255), 2, 8, 0 );

         //display coordinates
         printf("x: %d y: %d r: %d\n",center.x,center.y, radius);
    }

    //create window
    cvNamedWindow("circles", 1);
    cvNamedWindow("SnookerImage", 1);
    //show image in window
    cvShowImage("circles", rgbcanny);
    cvShowImage("SnookerImage", img);

    cvSaveImage("out.png", rgbcanny);
    cvWaitKey(0);

    return 0;
}

Answer 1

如果每个球都有统一的颜色，您可以检查中心的颜色：

CvMemStorage* storage = cvCreateMemStorage(0);
cvSmooth(image, image, CV_GAUSSIAN, 5, 5 );
CvSeq* results = cvHoughCircles(
image,
storage,
CV_HOUGH_GRADIENT,
2,
image->width/10
);
for( int i = 0; i < results->total; i++ ) 
{
float* p = (float*) cvGetSeqElem( results, i );
CvPoint center = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
CvScalar c = cvGet2D(image, center.x, center.y); //color of the center
}

尚未测试代码，但应该没问题。

编辑：

哎呀，我忘记了 Get2D 方法中的一个参数，即从中获取颜色的实际图像。更改为正确的形式。

Answer 2

我们在开源视觉框架中编写了自己的斑点检测库：
http://www.simplecv.org

执行您想要的操作的代码非常简单：

img = Image("/path/to/image.png")
blobs = img.findBlobs()
circle_blobs = blobs.filter(blobs.isCircle() == True)
list_of_blobs_colors = circle_blobs.meanColor()