思路：

1、通過形態學操作、閾值處理、距離變換等方法，使得各個輪廓分開

2、計算輪廓數量

 1 #include <opencv2/opencv.hpp>
 2 #include <iostream>
 3 #include <math.h>
 4 
 5 using namespace cv;
 6 using namespace std;
 7 
 8 
 9 int main(int argc, char** argv)
10 {
11     Mat src = imread("計數.jpg");
12     //medianBlur(src, src,5);
 
//中值濾波，去除椒鹽噪聲
13     imshow("src", src);
14 
15     Mat src_gray,binary;
16     
17     cvtColor(src,src_gray,COLOR_BGR2GRAY);
18     
19     threshold(src_gray,binary,0,255,THRESH_BINARY|THRESH_TRIANGLE);//顏色單一時，使用THRESH_TRIANGLE比OTSU好
20     imshow("binary", binary);
21 
22     //形態學操作
23     Mat kernel = getStructuringElement(MORPH_RECT,Size(5
 
,5));
24     dilate(binary, binary, kernel,Point(-1,-1),4);
25 
26     //距離變換
27     Mat dist;
28     bitwise_not(binary, binary);//取反
29     distanceTransform(binary,dist,CV_DIST_L2,3);
30     normalize(dist, dist,0,1.0,NORM_MINMAX);
31     imshow("dist", dist);
32 
33     //閾值化二值分割
34     //threshold(dist, dist,0.7,1.0,THRESH_BINARY);
 
//對距離進行篩選，去除邊緣部分
35     //normalize(dist, dist, 0, 255, NORM_MINMAX);
36     Mat dist_8U;
37     dist.convertTo(dist_8U,CV_8U);
38     adaptiveThreshold(dist_8U, dist_8U, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 85, 0.0);//自適應閾值，代替上面的閾值操作
39     //形態學操作，使得斷開部分連接
40     kernel = getStructuringElement(MORPH_RECT, Size(5, 5), Point(-1, -1));
41     dilate(dist_8U, dist_8U, kernel, Point(-1, -1),3);
42 
43     imshow("dist_8U", dist_8U);
44 
45     // 連通區域計數
46     vector<vector<Point>> contours;
47     findContours(dist_8U, contours, CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
48 
49     // draw result
50     Mat markers = Mat::zeros(src.size(), CV_8UC3);
51     RNG rng(12345);
52     for (size_t t = 0; t < contours.size(); t++) {
53         drawContours(markers, contours, static_cast<int>(t), Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)),
54             -1, 8, Mat());
55     }
56     printf("number of corns : %d", contours.size());
57     imshow("Final result", markers);
58 
59     waitKey(0);
60 
61     return 0;
62 }

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace cv;
using namespace std;


int main(int argc, char** argv)
{
Mat src = imread("計數.jpg");
//medianBlur(src, src,5);//中值濾波，去除椒鹽噪聲
imshow("src", src);

Mat src_gray,binary;

cvtColor(src,src_gray,COLOR_BGR2GRAY);

threshold(src_gray,binary,0,255,THRESH_BINARY|THRESH_TRIANGLE);//顏色單一時，使用THRESH_TRIANGLE比OTSU好
imshow("binary", binary);

//形態學操作
Mat kernel = getStructuringElement(MORPH_RECT,Size(5,5));
dilate(binary, binary, kernel,Point(-1,-1),4);

//距離變換
Mat dist;
bitwise_not(binary, binary);//取反
distanceTransform(binary,dist,CV_DIST_L2,3);
normalize(dist, dist,0,1.0,NORM_MINMAX);
imshow("dist", dist);

//閾值化二值分割
//threshold(dist, dist,0.7,1.0,THRESH_BINARY);//對距離進行篩選，去除邊緣部分
//normalize(dist, dist, 0, 255, NORM_MINMAX);
Mat dist_8U;
dist.convertTo(dist_8U,CV_8U);
adaptiveThreshold(dist_8U, dist_8U, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 85, 0.0);//自適應閾值，代替上面的閾值操作
//形態學操作，使得斷開部分連接
kernel = getStructuringElement(MORPH_RECT, Size(5, 5), Point(-1, -1));
dilate(dist_8U, dist_8U, kernel, Point(-1, -1),3);

imshow("dist_8U", dist_8U);

// 連通區域計數
vector<vector<Point>> contours;
findContours(dist_8U, contours, CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);

// draw result
Mat markers = Mat::zeros(src.size(), CV_8UC3);
RNG rng(12345);
for (size_t t = 0; t < contours.size(); t++) {
drawContours(markers, contours, static_cast<int>(t), Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)),
-1, 8, Mat());
}
printf("number of corns : %d", contours.size());
imshow("Final result", markers);

waitKey(0);

return 0;
}

opencv——對象計數