使用Opencv和Hough变换圆检测圆（下标错误）

Question

我尝试过各种演示代码，如“opencv查找：轮廓”，模板匹配（效果不好，因为它无法检测到顶盖的旋转）

我发现最好的方法是将Canny边缘检测和Hough变换圆相结合，这样Canny边缘检测的输出结果可以是Hough变换圆的输入图像，结果如下。

不幸的是，并非所有圆圈都被检测到，如果我更改

for（int i=0； i

for (int i = 0; i < 24; i++) // 24 is the no. of cans

我将得到一个表达式：向量下标超出范围。我不知道为什么它只能检测到21个圆圈

源代码如下：-

using namespace cv;
using namespace std;
Mat src, src_gray;

int main()
{
Mat src1;

src1 = imread("cans.jpg", CV_LOAD_IMAGE_COLOR);
namedWindow("Original image", CV_WINDOW_AUTOSIZE);
imshow("Original image", src1);


Mat gray, edge, draw;
cvtColor(src1, gray, CV_BGR2GRAY);

Canny(gray, edge,50, 150, 3);
//50,150,3

edge.convertTo(draw, CV_8U);
namedWindow("Canny Edge", CV_WINDOW_AUTOSIZE);
imshow("Canny Edge", draw);
imwrite("output.jpg", draw);


waitKey(500);




/// Read the image
src = imread("output.jpg", 1);
Size size(932, 558);//the dst image size,e.g.100x100
resize(src, src, size);//resize image

/// Convert it to gray
cvtColor(src, src_gray, CV_BGR2GRAY);

/// Reduce the noise so we avoid false circle detection
GaussianBlur(src_gray, src_gray, Size(9, 9), 2, 2);

vector<Vec3f> circles;

/// Apply the Hough Transform to find the circles
HoughCircles(src_gray, circles, CV_HOUGH_GRADIENT, 1, src_gray.rows / 8,200, 100, 0, 0);

/// Draw the circles detected
for (int i = 0; i < circles.size(); i++)
{
    printf("are you um?\n");
    Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
    int radius = cvRound(circles[i][2]);
    // circle center
    circle(src, center, 3, Scalar(0, 255, 0), -1, 8, 0);
    // circle outline
    circle(src, center, radius, Scalar(255, 0, 255), 3, 8, 0);
}

//  namedWindow("Hough Circle Transform Demo", CV_WINDOW_NORMAL);
    imshow("Hough Circle Transform Demo", src);
    line(src, Point(0, 288), Point(1024, 288), Scalar(225, 220, 225), 2, 8);
    // middle line
    line(src, Point(360, 0), Point(360, 576), Scalar(225, 220, 225), 2, 8);
    //break cans into 4 by 4
    line(src, Point(600, 0), Point(600, 576), Scalar(225, 220, 225), 2, 8);
                             //      x, y  
    imshow("Lines", src);
    imwrite("lineoutput.jpg", src);


    waitKey(0);


    return 0;
}