opencv3计算图像中轮廓的长度-滚动条

#include<iostream>
#include<opencv2/opencv.hpp>
#include<vector>

using namespace cv;
using namespace std;

Mat grayImage, cannyImage;
int g_nMinThred = 128, g_nMaxThred = 255;

//有滚动条事件时，可以进入回调函数
void on_Trackbar(int, void *)
{
//为了得到二值图像，对灰度图进行边缘检测
Canny(grayImage, cannyImage, g_nMinThred, g_nMaxThred, 3);
//在得到的二值图像中寻找轮廓
vector<vector<Point>> contours;
vector<Vec4i> hierarchy;
findContours(cannyImage, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));

//绘制轮廓
for (int i = 0; i < (int)contours.size(); i++)
{
drawContours(cannyImage, contours, i, Scalar(255), 1, 8);
}

//计算轮廓的长度
for (int i = 0; i < (int)contours.size(); i++)
{
double g_dConLength = arcLength(contours[i], true);
cout << "【用轮廓长度计算函数计算出来的第" << i << "个轮廓的长度为：】" << g_dConLength << endl;
}

imshow("【处理后的图像】", cannyImage);
}

int main()
{
Mat srcImage = imread("group.jpg");
namedWindow("【原图】", 0);
imshow("【原图】", srcImage);

//首先对图像进行空间的转换
cvtColor(srcImage, grayImage, CV_BGR2GRAY);
//对灰度图进行滤波
GaussianBlur(grayImage, grayImage, Size(3, 3), 0, 0);
imshow("【滤波后的图像】", grayImage);

createTrackbar("min", "【原图】", &g_nMinThred, 255, on_Trackbar);
on_Trackbar(g_nMinThred, 0);
createTrackbar("max", "【原图】", &g_nMaxThred, 255, on_Trackbar);
on_Trackbar(g_nMaxThred, 0);

waitKey(0);

return 0;
}