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

using namespace cv;
using namespace std;

Mat src,dst;
void contours(int, void*);
int thresholdMax = 255;
int thresholdvalue = 100;
int main(int argc, char** argv)
{
	src = imread("D:/test/fish.png");
	if (!src.data)
 

	{
		printf("圖片為空");
		return -1;
	}
	cvtColor(src, dst, CV_BGR2GRAY);
	namedWindow("output image");
	createTrackbar("Canny thresh", "output image", &thresholdvalue, thresholdMax, contours);
	contours(0,0);
	imshow("input image", src);
	waitKey(0);
	return 0;
}

void contours(int, void *)
{
	Mat canny_output;
 

	dst = Mat::zeros(src.size(), CV_8UC3);
	vector<vector<Point>> contours;
	vector<Vec4i> hierachy;
	/*邊緣檢測，thresholdvalue，thresholdvalue*2這兩個引數比值一般來說是1:1.5、1:2、1:3*/
	Canny(src, canny_output, thresholdvalue, thresholdvalue * 2, 3, false);
	findContours(canny_output, contours, hierachy,
 
 RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
	RNG rng(12345);
	for (size_t i = 0; i < contours.size(); i++)
	{
		Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255),rng.uniform(0, 255));
		drawContours(dst, contours, (int)i, color, 1, LINE_AA, hierachy, 0, Point(0, 0));

	}
	imshow("output image", dst);
}

大致步驟：

1. 先將圖片轉化為灰度影象
2. 進行邊緣檢測
3. 找到輪廓findContours
4. 繪製輪廓drawContours

執行結果：