opencv3检测凸包convexHull函数-使用方式二-滚动条

来源：互联网发布：数据库查询语句大全编辑：程序博客网时间：2024/05/16 13:04
#include<opencv2/opencv.hpp>#include<iostream>#include<vector>using namespace cv;using namespace std;int g_nMinThred = 125;int g_nMaxThred = 255;int g_nColor = 255;int g_CheckWay = 0;int g_nThick = 0;int main(){RNG &rng = theRNG();Mat srcImage = imread("group.jpg");imshow("【原图】", srcImage);//因为后期需要在二值图像中寻找轮廓，所以需要进行阀值操作或是使用canny边缘检测操作，无论是哪种方式，都需要输入一张灰度图像//所以这里先进行图像格式的转换Mat grayImage;cvtColor(srcImage, grayImage, CV_BGR2GRAY);//处理图像之前先对图像进行滤波操作Mat blurImage;GaussianBlur(grayImage, blurImage, Size(3, 3), 0, 0);imshow("【高斯滤波后的灰度图】", blurImage);namedWindow("【滚动条窗口】", 0);createTrackbar("MinThred", "【滚动条窗口】", &g_nMinThred, 255, 0);createTrackbar("MaxThred", "【滚动条窗口】", &g_nMaxThred, 255, 0);createTrackbar("Color", "【滚动条窗口】", &g_nColor, 255, 0);createTrackbar("CheckWay", "【滚动条窗口】", &g_CheckWay, 2, 0);createTrackbar("thick", "【滚动条窗口】", &g_nThick, 100, 0);char key;while (1){//这里采用边缘检测的方式来生成二值图像Mat cannyImage;Canny(blurImage, cannyImage, g_nMinThred + 1, g_nMaxThred + 1);//在得到的二值图像中寻找轮廓//g_vcontours用来存储 所有轮廓 的 点向量vector<vector<Point>> g_vcontours;vector<Vec4i> g_vHierarchy;findContours(cannyImage, g_vcontours, g_vHierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));//在被找到的所有轮廓的点向量中，寻找凸包//g_vHull用来存储 所有凸包检测的凸包 的点集    ，注意：这里的g_vHull变量需要确定大小，保证输入和输出的大小相同vector<vector<Point>> g_vHull(g_vcontours.size());for (int i = 0; i < (int)g_vcontours.size(); i++){convexHull(g_vcontours[i], g_vHull[i], true);}//首先建立一个黑色背景Mat dstImage = Mat::zeros(srcImage.size(), CV_8UC1);for (int i = 0; i < (int)g_vcontours.size(); i++){//如果g_CheckWay变量是0，表示轮廓和凸包都显示，如果是1  仅仅显示轮廓，  如果是2   仅仅显示凸包if (g_CheckWay == 0){//用drawContours函数先绘制所有轮廓drawContours(dstImage, g_vcontours, i, Scalar(g_nColor), g_nThick + 1, 8);//用drawContours函数绘制所有的凸包drawContours(dstImage, g_vHull, i, Scalar(g_nColor), g_nThick + 1, 8);}if (g_CheckWay == 1){//用drawContours函数先绘制所有轮廓drawContours(dstImage, g_vcontours, i, Scalar(g_nColor), g_nThick + 1, 8);}if (g_CheckWay == 2){//用drawContours函数绘制所有的凸包drawContours(dstImage, g_vHull, i, Scalar(g_nColor), g_nThick + 1, 8);}}imshow("【处理后的图像】", dstImage);key = waitKey(1);if (key == 27)break;}return 0;}
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