Greetings!
With the below C-code I'm detecting arches within an image with 2 arches. I'm using opencv-4.1.0 on a windows-10 machine, if this matters.
Using the parameters
int dp = 3; // The inverse ratio of resolution;
int min_dist = 1000; // Minimum distance between detected centers
int upper_canny = 65; // Upper threshold for the internal Canny edge detector
int th_center = 85; // Threshold for center detection
int min_radius = 1000;
int max_radius = 0;
I find 5 circles and they outline more or less accurately the arc.
Playing with dp, and th_center I get different results.
What wolud be an appropriate approach to get unambiguous results?
Thanks for hints
Wolf
#include <windows.h>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
int main(int argc, char** argv) {
char ImageName[256]={0};
int big_h=1024*8;
int big_w=1280, h=550;
int cx=(1280/2)-(big_w/2);
int cy=big_h-h;
cv::Rect roi(cx, 0, big_w, h);
cv::Mat input, filter, gray, canny;
cv::Mat big_gray(big_h, big_w, CV_8U);
strcpy(ImageName, "D:/CircleTestImage03.jpg");
// Read image
input = cv::imread(ImageName, cv::IMREAD_COLOR);
if (!input.data ) {
printf("Image '%s' not found\n", ImageName);
return(-1);
}
// Convert to gray
cv::cvtColor(input(roi), gray, cv::COLOR_BGR2GRAY);
cv::imshow("gray", gray);
// Reduce the noise avoiding false circle detection
cv::GaussianBlur(gray, gray, cv::Size(9, 9), 2, 2);
cv::imshow("Blur", gray);
// Place gray to bottom of big_gray allowing center finding of bog circeles.
// Otherwise no arc will be found.
gray.copyTo(big_gray(cv::Rect(0,cy, big_w, gray.rows)));
int dp = 3; // The inverse ratio of resolution;
int min_dist = 1000; // Minimum distance between detected centers
int upper_canny = 65; // Upper threshold for the internal Canny edge detector
int th_center = 85; // Threshold for center detection
int min_radius = 1000;
int max_radius = 0;
// Compute canny, info only
cv::Canny(gray, canny, upper_canny, upper_canny/2);
cv::imshow("canny", canny);
std::vector<cv::Vec3f> circles; // x, y, r
HoughCircles(big_gray, circles, cv::HOUGH_GRADIENT, dp, min_dist, upper_canny, th_center, min_radius, max_radius);
// Draw circles detected
for (int i = 0; i < (int)circles.size(); i++ ) {
// coordinates of outline within input framre
circles[i][0] += cx;
circles[i][1] -= cy;
cv::Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
int radius = cvRound(circles[i][2]);
printf("Circle #%d dp=%d x=%d y=%d r=%d\n", i, dp, center.x, center.y, radius);
cv::circle(input, center, radius, CV_RGB(255,0,0), 2, 8, 0 );
}
cv::imshow("input", input); cv::waitKey(1);
printf("Push key to finish.\n");
cv::waitKey(-1);
return 0;
}
