opencv学习之路（27）、轮廓查找与绘制（六）——外接圆、椭圆拟合、逼近多边形曲线、计算轮廓面积及长度、提取不规则轮廓

一、最小外接圆

 #include "opencv2/opencv.hpp"
 #include<iostream>
 using namespace std;
 using namespace cv;

 void main() {
     Mat srcImg = imread("E://10.png");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();
     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     Canny(srcImg, srcImg, , );
     imshow("Canny", srcImg);

     //查找轮廓
     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);
     cout << "num=" << contours.size() << endl;

     Point2f center;  //定义圆中心坐标
     float radius;  //定义圆半径
     for (int i = ; i<contours.size(); i++)  //依次遍历每个轮廓
     {
         minEnclosingCircle(Mat(contours[i]), center, radius);
         drawContours(dstImg, contours, i, Scalar(, , ), , );
         circle(dstImg, center, radius, Scalar(, , ), , );  //绘制第i个轮廓的最小外接圆
     }
     imshow("dst", dstImg);

     waitKey();
 }

二、椭圆拟合

 #include "opencv2/opencv.hpp"
 using namespace cv;

 void main() {
     Mat srcImg = imread("E://10.png");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();
     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     Canny(srcImg, srcImg, , );
     imshow("Canny", srcImg);

     //查找轮廓
     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);

     vector<RotatedRect> box(contours.size());
     Point2f rect[];
     for (int i = ; i<contours.size(); i++)
     {
         box[i] = fitEllipse(Mat(contours[i]));
         //ellipse(dstImg, box[i].center, Size(box[i].size.width/2, box[i].size.height/2), box[i].angle, 0, 360, Scalar(0, 255, 0), 2, 8);
         ellipse(dstImg, box[i], Scalar(, , ), , );
     }
     imshow("dst", dstImg);

     waitKey();
 }

三、逼近多边形曲线

 #include "opencv2/opencv.hpp"
 using namespace cv;

 void main() {
     Mat srcImg = imread("E://02.jpg");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();
     Mat dstImg2(srcImg.size(), CV_8UC3, Scalar::all());//全黑图像

     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     //Canny(srcImg, srcImg, 100, 200);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY_INV);
     imshow("threshold", srcImg);

     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);
     vector<vector<Point>> contours_poly(contours.size());

     for (int i = ; i<contours.size(); i++)
     {
         approxPolyDP(Mat(contours[i]), contours_poly[i],, true);//true曲线封闭，反之不封闭
         drawContours(dstImg, contours, i, Scalar(, , ), , );//绘制轮廓
         drawContours(dstImg2, contours_poly, i, Scalar(, , ), , );  //绘制多边形逼近
     }
     imshow("dst", dstImg);
     imshow("approx", dstImg2);

     waitKey();
 }

四、计算轮廓面积及长度（可用于轮廓筛选）

 #include "opencv2/opencv.hpp"
 #include<iostream>
 using namespace std;
 using namespace cv;

 void main() {
     Mat srcImg = imread("E://33.jpg");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();
     Mat dstImg2(srcImg.size(), CV_8UC3, Scalar::all());

     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     //Canny(srcImg, srcImg, 100, 200);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY);
     imshow("threshold", srcImg);

     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);
     cout << "num=" << contours.size() << endl;

     for (int i = ; i<contours.size(); i++)
     {
         double area = contourArea(contours[i]);//计算第i个轮廓的面积
         cout<<"area--"<<i<<"---"<<area<<endl;

         double length = arcLength(contours[i], true);
         cout << "length--" << i << "---" << length << endl;
         //if(area>10000)  //面积大约1W
         //if(area> 100 && area<300)

         if (length< && area>)
             drawContours(dstImg, contours, i, Scalar(, , ), , );
     }
     imshow("dst", dstImg);
     waitKey();
 }

五、提取不规则轮廓

 #include "opencv2/opencv.hpp"
 using namespace cv;

 void main() {
     Mat srcImg = imread("E://220.jpg");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();  //原图备份
     Mat tempImg = srcImg.clone();  //原图备份
     Mat tempImg2(srcImg.size(), CV_8UC3, Scalar::all());  //定义全黑的和原图一样大小的图像
     Mat draw(srcImg.size(), CV_8UC3, Scalar::all());
     Mat tempImg3(srcImg.size(), CV_8UC3, Scalar::all()); 

     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY); //二值化
     imshow("threshold", srcImg);

     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);
     while ()
     {
         for (int i = ; i<contours.size(); i++)
         {
             tempImg2.copyTo(draw);  //每次进入将draw清空为全黑
             tempImg2.copyTo(tempImg3);
             //drawContours(dstImg, contours, i, Scalar(0, 255, 0), 5, 8);
             drawContours(draw, contours, i, Scalar(, , ), -, );
             Mat mask;  //定义掩码
             cvtColor(draw, mask, CV_BGR2GRAY);
             tempImg.copyTo(tempImg3, mask);  //将tempImg 复制到tempImg3(只有mask部分被复制)
             imshow("draw", draw);
             imshow("result", tempImg3);
             char key = waitKey();
             if (key == )  //按下Esc键跳出for循环
                 break;
         }
         break;
     }
 }