opencvapproxDP多边形逼近获取四边形轮廓信息

[opencv]approxDP多边形逼近获取四边形轮廓信息#include"opencv2/opencv.hpp"#include<iostream>#include<math.h>#includestring.h>usingnamespacecv;usingnamespacestd;intthresh=50,N=11;constchar*wndname="SquareDetectionDemo";intcalcdistance(Point_<int>&point1,Point_<int>point2){intx1=point1.x;inty1=point1.y;intx2=point2.x;inty2=point2.y;intdist=sqrt(pow(x2-x1,2)+pow(y2-x1,2));returndist;}//查找向量之间的⾓度余弦//pt0->pt1pt0->pt2staticdoubleangle(Pointpt1,Pointpt2,Pointpt0){doubledx1=pt1.x-pt0.x;doubledy1=pt1.y-pt0.y;doubledx2=pt2.x-pt0.x;doubledy2=pt2.y-pt0.y;return(dx1*dx2+dy1*dy2)/sqrt((dx1*dx1+dy1*dy1)*(dx2*dx2+dy2*dy2)+1e-10);//cos<a,b>=(ab)/(|a||b|)}//返回图像上检测到的正⽅形序列//序列存储在指定的内存存储器中staticvoidfindSquares(constMat&image,vector<vector<Point>>&squares){inth=image.rows;intw=image.cols;squares.clear();Matpyr,timg,gray0(image.size(),CV_8U),gray;//缩⼩和放⼤图像以滤除噪⾳pyrDown(image,pyr,Size(image.cols/2,image.rows/2));//⾼斯降噪，并只取奇数⾏列缩⼩图⽚pyrUp(pyr,timg,image.size());//插⼊偶数⾏列，再次⾼斯降噪vector<vector<Point>>contours;//在图像的每个颜⾊平⾯中查找正⽅形for(intc=0;c<3;c++){intch[]={c,0};mixChannels(&timg,1,&gray0,1,ch,1);//尝试⼏个阈值级别for(intl=0;l<N;l++){if(l==0){Canny(gray0,gray,0,thresh,5);dilate(gray,gray,Mat(),Point(-1,-1));}else{//applythresholdifl!=0://tgray(x,y)=gray(x,y)<(l+1)*255/N?255:0gray=gray0>=(l+1255/N;}//_RETR_LIST参数指明最后只存了⾓点位置findContours(gray,contours,RETR_LIST,CHAIN_APPROX_SIMPLE);vector<Point>approx;//testeachcontour//⼀次取⼀个轮廓判断下是不是矩形for(size_ti=0;i<contours.size();i++){//approx存储了近似后的轮廓approxPolyDP(Mat(contours[i]),approx,arcLength(Mat(contours[i]),true0.02,true);if(approx.size()==4&&//矩形必须是四个点fabs(contourArea(Mat(approx)))>5000&&isContourConvex(Mat(approx)))//必须是凸的，咋理解{doublemaxCosine=0;for(intj=2;j<5;j++){//findthemaximumcosineoftheanglebetweenjointedgesdoublecosine=fabs(angle(approx[j%4],approx[j-2],approx[j-1]));maxCosine=MAX(maxCosine,cosine);}//1,2,3顶点的⾓余弦，最⼤的余弦值，对应三个⾓中的最⼩⾓，也就是三个⾓中，最不像直⾓的//为什么是三个呢？三个中最不像直⾓的都接近直⾓了，剩下的⾃然也是直⾓if(maxCosine<0.3)if(calcdistance(approx[0],approx[3])<h&&calcdistance(approx[0],approx[1])<w){squares.push_back(approx);}}}}}}//函数绘制图像中的所有四边形staticvoiddrawSquares(Mat&image,constvector<vector<Point>>&squares){for(size_ti=0;i<squares.size();i++){constPoint*p=&squares[i][0];intn=(int)squares[i].size();circle(image,squares[i][0],3,Scalar(0,0,255),1);circle(image,squares[i][1],3,Scalar(0,0,255),1);circle(image,squares[i][2],3,Scalar(0,0,255),1);circle(image,squares[i][3],3,Scalar(0,0,255),1);////polylines(image,&p,&n,1,true,Scalar(0,255,0),1,LINE_AA);break;Rectrr=boundingRect(squares[i]);//通过最⼩包围盒来获取主要函数区域vector<vector<Point>>main;main[0][0]=squares[0][0];main[0][1]=squares[0][1];main[0][2]=squares[1][2];main[0][3]=squares[1][3];circle(image,main[0][0],1,Scalar(0,255,0),-1);circle(image,main[0][1],1,Scalar(0,255,0),-1);imshow("main",image);RotatedRectminRect=minAreaRect(Mat(main[0]));Point2fvertex[4];//⽤于存放最⼩矩形的四个顶点minRect.points(vertex);//vertex//绘制最⼩⾯积包围矩形vector<Point>min_rectangle;for(inti=0;i<4;){line(image,vertex[i],vertex[(i+1)%4],Scalar(0,255,255),1,8);//⾮常巧妙的表达式min_rectangle.push_back(vertex[i]);//Pointvector容器中}////////rectangle(image,Point(rr.x,rr.y),Point(rr.x+rr.width,rr.y+rr.height),1);floatarea=contourArea(squares[i],false);cout<<"area=="<<area<<endl;break;}imshow(wndname,image);}intmain(int/*argc*/,char**/*argv*/){Matimage=imread("/home/leoxae/KeekoRobot/TestPic//1.png");vector<vector<Point>>squares;findSquares(image,squares);for(autoitx=squares.begin();itx!=squares.end();itx++){vector<Point>points=*itx;cout<<"Pts="<<points<<endl;}/*Pointb_tl=squares[0][0];Pointb_tr=squares[0][1];Pointb_bl=squares[0][2];Pointb_br=squares[0][3];Points_tl=squares[1][0];Points_tr=squares[1][1];Points_bl=squares[1][2];Points_br=squares[1][3];cout<<"b_tl=="<<b_tl<<endl;cout<<"b_tr=="<<b_tr<<endl;cout<<"b_bl=="<<b_bl<<endl;cout<<"b_br=="<<b_br<<endl;cout<<"s_tl=="<<s_tl<<endl;cout<<"s_tr=="<<s_tr<<endl;cout<<"s_bl=="<<s_bl<<endl;cout<<"s_br=="<<s_br<<endl;circle(image,b_bl,3,Scalar(0,0,255),-1);circle(image,b_tr,3,Scalar(0,0,255),-1);circle(image,b_bl,3,Scalar(0,0,255),-1);circle(image,b_br,3,Scalar(0,0,255),-1);circl