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我需要检测使用了opencv2中可用的HoughCircle函数的眼睛图片的虹膜。所以,在opencv for irc中使用hough circle函数查找分钟圆圈
// Read the image
src = imread("D:/001R_3.png");
if(!src.data)
{ return -1; }
/// 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);
/////////////
/// Generate grad_x and grad_y
Mat grad_x, grad_y;
Mat abs_grad_x, abs_grad_y;
Sobel(src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT);
convertScaleAbs(grad_x, abs_grad_x);
/// Gradient Y
//Scharr(src_gray, grad_y, ddepth, 0, 1, scale, delta, BORDER_DEFAULT);
Sobel(src_gray, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT);
convertScaleAbs(grad_y, abs_grad_y);
/// Total Gradient (approximate)
addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);
///////////////
vector<Vec3f> circles;
/// Apply the Hough Transform to find the circles
HoughCircles(grad, circles, CV_HOUGH_GRADIENT, 1, grad.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][1]));
cout<<center;
int radius = cvRound(circles[i][2]);
// circle center
cout<<radius;
circle(src, center, 3, Scalar(0,255,0), -1, 8, 0);
// circle outline
circle(src, center, radius, Scalar(0,0,255), 3, 8, 0);
}
/// Show your results
namedWindow("Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE);
imshow("Hough Circle Transform Demo",src);
}
因此,这里是我的代码,只检测眼睛的外侧部分,其中,因为我想瞳孔和虹膜边界进行检测和那没有发生,我提到的链接OpenCV: Using Hough Circle Transformation to detect iris 但不这样工作。而不是canny边缘检测器使用sobel。建议请。