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original image 我試圖檢測此圖像中連接邊界的集羣。我需要找到這些邊緣的長度以及各個簇的回轉半徑。 我使用的是opencv 2.4.13。 我使用下面的代碼來檢測使用輪廓的質量簇。檢測邊緣（連接的邊緣）並查找邊緣長度和連接的組件回轉半徑
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);
/// Function header
void thresh_callback(int, void*);
/** @function main */
int main(int argc, char** argv)
{
/// Load source image and convert it to gray
src = imread(argv[1], 1);
/// Convert image to gray and blur it
cvtColor(src, src_gray, CV_BGR2GRAY);
blur(src_gray, src_gray, Size(3,3));
/// Create Window
char* source_window = "Source";
namedWindow(source_window, CV_WINDOW_AUTOSIZE);
imshow(source_window, src);
createTrackbar(" Canny thresh:", "Source", &thresh, max_thresh, thresh_callback);
thresh_callback(0, 0);
waitKey(0);
return(0);
}
/** @function thresh_callback */
void thresh_callback(int, void*)
{
Mat canny_output;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
/// Detect edges using canny
Canny(src_gray, canny_output, thresh, thresh*2, 3);
/// Find contours
findContours(canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
/// Get the moments
vector<Moments> mu(contours.size());
for(int i = 0; i < contours.size(); i++)
{ mu[i] = moments(contours[i], false); }
/// Get the mass centers:
vector<Point2f> mc(contours.size());
for(int i = 0; i < contours.size(); i++)
{ mc[i] = Point2f(mu[i].m10/mu[i].m00 , mu[i].m01/mu[i].m00); }
/// Draw contours
Mat drawing = Mat::zeros(canny_output.size(), CV_8UC3);
Mat drawing2 = Mat::zeros(canny_output.size(), CV_8UC3);
for(int i = 0; i< contours.size(); i++)
{if(arcLength(contours[i], true)>900)
{Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255));
drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
circle(drawing, mc[i], 4, color, -1, 8, 0);}
}
int length=0;
int j=0;
for(int i = 0; i< contours.size(); i++)
{
if(arcLength(contours[i], true)>length)
{
length=arcLength(contours[i], true);
j=i;
}
}
Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255));
drawContours(drawing2, contours, j, color, 2, 8, hierarchy, 0, Point());
circle(drawing2, mc[j], 4, color, -1, 8, 0);
/// Show in a window
namedWindow("Contours", CV_WINDOW_AUTOSIZE);
imshow("Contours", drawing);
namedWindow("Contours2", CV_WINDOW_AUTOSIZE);
imshow("Contours_max", drawing2);
/// Calculate the area with the moments 00 and compare with the result of the OpenCV function
printf("\t Info: Area and Contour Length \n");
for(int i = 0; i< contours.size(); i++)
{
if(arcLength(contours[i], true)>900)
{printf(" * Contour[%d] - Area (M_00) = %.2f - Area OpenCV: %.2f - Length: %.2f \n", i, mu[i].m00, contourArea(contours[i]), arcLength(contours[i], true));
Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255));
drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
circle(drawing, mc[i], 4, color, -1, 8, 0);}
}
}
問題是輪廓對於共同的共享邊緣而言變得不同，並且邏輯上它們應該是同一個羣集。以下輪廓圖像我給。 contour extracted above a certain length
我們可以看到，具有相同共享邊的許多輪廓被分別視爲不同的輪廓。我希望他們作爲相同邊界羣的一部分。還建議我如何檢測邊界的長度和回轉半徑。 請幫忙。