opencv学习之路（26）、轮廓查找与绘制（五）——最小外接矩形

一、简介

二、轮廓最小外接矩形的绘制

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

 void main()
 {
     //轮廓最小外接矩形的绘制
     Mat srcImg = imread("E://00.png");
     Mat dstImg = srcImg.clone();
     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_EXTERNAL, CV_CHAIN_APPROX_NONE);
     vector<Rect> boundRect(contours.size());  //定义外接矩形集合
     vector<RotatedRect> box(contours.size()); //定义最小外接矩形集合
     Point2f rect[];
     for(int i=; i<contours.size(); i++)
     {
         box[i] = minAreaRect(Mat(contours[i]));  //计算每个轮廓最小外接矩形
         boundRect[i] = boundingRect(Mat(contours[i]));
         circle(dstImg, Point(box[i].center.x, box[i].center.y), , Scalar(, , ), -, );  //绘制最小外接矩形的中心点
         box[i].points(rect);  //把最小外接矩形四个端点复制给rect数组
         rectangle(dstImg, Point(boundRect[i].x, boundRect[i].y), Point(boundRect[i].x + boundRect[i].width, boundRect[i].y + boundRect[i].height), Scalar(, , ), , );
         for(int j=; j<; j++)
         {
             line(dstImg, rect[j], rect[(j+)%], Scalar(, , ), , );  //绘制最小外接矩形每条边
         }
     }
     imshow("dst", dstImg);
     waitKey();
 }

三、粗略计算物体像素长宽

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

 void main()
 {
     Mat srcImg = imread("E://cup.jpg");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();
     medianBlur(srcImg, srcImg, );
     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY_INV); //INV是因为背景白色，物体黑色，需要反转一下
     imshow("threshold", srcImg);

     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;

     findContours(srcImg, contours, hierarcy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
     cout<<"num="<<contours.size()<<endl;
     vector<Rect> boundRect(contours.size());
     vector<RotatedRect> box(contours.size());
     Point2f rect[];
     for(int i=; i<contours.size(); i++)
     {
         box[i] = minAreaRect(Mat(contours[i]));
         boundRect[i] = boundingRect(Mat(contours[i]));
         cout<<box[i].angle<<endl;
         cout<<box[i].center<<endl;
         cout<<box[i].size.width<<endl;
         cout<<box[i].size.height<<endl;
         circle(dstImg, Point(box[i].center.x, box[i].center.y), , Scalar(, , ), -, );

         //绘制外接矩形和    最小外接矩形（for循环）
         rectangle(dstImg, Point(boundRect[i].x, boundRect[i].y), Point(boundRect[i].x + boundRect[i].width, boundRect[i].y + boundRect[i].height), Scalar(, , ), , );
         box[i].points(rect);//把最小外接矩形四个端点复制给rect数组
         for(int j=; j<; j++)
         {
             line(dstImg, rect[j], rect[(j+)%], Scalar(, , ), , );
         }

         char width[], height[];
         sprintf(width, "width=%0.2f", box[i].size.width);
         sprintf(height, "height=%0.2f", box[i].size.height);
         putText(dstImg, width, Point(, ), CV_FONT_HERSHEY_COMPLEX_SMALL, 0.85, Scalar(, , ));
         putText(dstImg, height, Point(, ), CV_FONT_HERSHEY_COMPLEX_SMALL, 0.85, Scalar(, , ));

     }
     imshow("dst", dstImg);
     waitKey();
 }

四、倾斜物体矫正提取

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

 void main()
 {
     Mat srcImg = imread("E://qrcode.jpg");
     imshow("src", srcImg);
     Mat dstImg = srcImg.clone();
     GaussianBlur(srcImg, srcImg, Size(, ), , );
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     Canny(srcImg, srcImg, , );//因为原图比较复杂，所以需要将canny的值调大，去除不想要的成分
     //threshold(srcImg, srcImg, 100, 255, CV_THRESH_BINARY_INV); //二值化也可以实现canny效果,不过在本例中杂絮较多
     imshow("canny", srcImg);
     Mat element = getStructuringElement(MORPH_RECT, Size(, ), Point(-, -)); //定义结构元素
     dilate(srcImg, srcImg, element); //膨胀
     imshow("dilate", srcImg);
     erode(srcImg, srcImg, element);
     imshow("erode", srcImg);

     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);
     vector<Rect> boundRect(contours.size());
     vector<RotatedRect> box(contours.size());
     Point2f rect[];
     for(int i=; i<contours.size(); i++)
     {
         box[i] = minAreaRect(Mat(contours[i]));
         boundRect[i] = boundingRect(Mat(contours[i]));

         if(box[i].size.width <  || box[i].size.height<)//筛选
             continue;
         rectangle(dstImg, Point(boundRect[i].x, boundRect[i].y), Point(boundRect[i].x + boundRect[i].width, boundRect[i].y + boundRect[i].height), Scalar(, , ), , );
         circle(dstImg, Point(box[i].center.x, box[i].center.y), , Scalar(, , ), -, );
         box[i].points(rect);
         for(int j=; j<; j++)
         {
             line(dstImg, rect[j], rect[(j+)%], Scalar(, , ), , );
         }

         float angle;
         cout<<"angle="<<box[i].angle<<endl;
         angle = box[i].angle;
         char width[], height[];
         sprintf(width, "width=%0.2f", box[i].size.width);
         sprintf(height, "height=%0.2f", box[i].size.height);
         putText(dstImg, width, Point(, ), CV_FONT_HERSHEY_COMPLEX_SMALL, 0.85, Scalar(, , ));
         putText(dstImg, height, Point(, ), CV_FONT_HERSHEY_COMPLEX_SMALL, 0.85, Scalar(, , ));
         imshow("temp", dstImg);

         //利用仿射变换进行旋转        另一种方法，透视变换
         if (< abs(angle) && abs(angle)<=)
             angle = angle;//负数，顺时针旋转
         else if (< abs(angle) && abs(angle)<)
             angle =  -  abs(angle);//正数，逆时针旋转
         Point2f center = box[i].center;  //定义旋转中心坐标
         double angle0 = angle;
         double scale = ;
         Mat roateM = getRotationMatrix2D(center, angle0, scale);  //获得旋转矩阵,顺时针为负，逆时针为正
         warpAffine(dstImg, dstImg, roateM, dstImg.size()); //仿射变换

         //保存二维码
         int x0=, y0=, w0=, h0=;
         x0 = boundRect[i].x;
         y0 = boundRect[i].y;
         w0 = boundRect[i].width;
         h0 = boundRect[i].height;
         Mat ROI = dstImg(Rect(x0, y0, w0, h0));
         imwrite("F://1.jpg", ROI);
     }
     imshow("dst", dstImg);
     waitKey();
 }