// 引入实际标定板方格宽度的标定程序 #include <string> #include <iostream> #include <cv.h> #include <highgui.h> using namespace std; int main() { CvCapture* capture; //摄像头指针 capture=cvCreateCameraCapture(0); if(capture==0){ printf("无法捕获摄像头设备！ "); return 0; }else{ printf("捕获摄像头设备成功！！ "); } IplImage* frame; //图像指针 cvNamedWindow("摄像机帧截取窗口",1); printf("按“C”键截取当前帧并保存为标定图片... 按“Q”键退出截取帧过程... "); int number_image=1; //文件名后的编号，从1开始，也是截取的图像帧数 char filename[20]=""; //保存文件名的字符串数组 while(true) { frame=cvQueryFrame(capture); if(!frame) break; cvShowImage("摄像机帧截取窗口",frame); if(cvWaitKey(10)=='c'){ sprintf (filename,"%d.jpg",number_image); cvSaveImage(filename,frame); cout<<"成功获取当前帧，并以文件名"<<filename<<"保存... "; printf("按“C”键截取当前帧并保存为标定图片... 按“Q”键退出截取帧过程... "); number_image++; }else if(cvWaitKey(10)=='q'){ printf("截取图像帧过程完成... "); cout<<"共成功截取"<<--number_image<<"帧图像！！ "; break; } } cvReleaseImage(&frame); cvReleaseCapture(&capture); cvDestroyWindow("摄像机帧截取窗口"); IplImage * show; //RePlay图像指针 cvNamedWindow("RePlay",1); int number_image_copy=number_image; //复制图像帧数 CvSize board_size=cvSize(7,7); //标定板角点数 CvSize2D32f square_size=cvSize2D32f(18.2,18.2); //cvSize2D32f( double width, double height );假设我的每个标定方格长宽都是1.82厘米 float square_length=square_size.width; //方格长度 float square_height=square_size.height; //方格高度 int board_width=board_size.width; //每行角点数 int board_height=board_size.height; //每列角点数 int total_per_image=board_width*board_height; //每张图片角点总数 int count; //存储每帧图像中实际识别的角点数 int found; //识别标定板角点的标志位 int step; //存储步长，step=successes*total_per_image; int successes=0; //存储成功找到标定板上所有角点的图像帧数 int a=1; //临时变量，表示在操作第a帧图像 CvPoint2D32f * image_points_buf = new CvPoint2D32f[total_per_image]; //存储角点图像坐标的数组 CvMat * image_points=cvCreateMat(number_image*total_per_image,2,CV_32FC1); //存储角点的图像坐标的矩阵 CvMat * object_points=cvCreateMat(number_image*total_per_image,3,CV_32FC1); //存储角点的三维坐标的矩阵 CvMat * point_counts=cvCreateMat(number_image,1,CV_32SC1); //存储每帧图像的识别的角点数 CvMat * intrinsic_matrix=cvCreateMat(3,3,CV_32FC1); //内参数矩阵 CvMat * distortion_coeffs=cvCreateMat(5,1,CV_32FC1); //畸变系数 while(a<=number_image_copy){ sprintf (filename,"%d.jpg",a); show=cvLoadImage(filename,-1); found=cvFindChessboardCorners(show,board_size,image_points_buf,&count, CV_CALIB_CB_ADAPTIVE_THRESH|CV_CALIB_CB_FILTER_QUADS); if(found==0){ //如果没找到标定板角点时 cout<<"第"<<a<<"帧图片无法找到棋盘格所有角点! "; cvNamedWindow("RePlay",1); cvShowImage("RePlay",show); cvWaitKey(0); }else{ //找到标定板角点时 cout<<"第"<<a<<"帧图像成功获得"<<count<<"个角点... "; cvNamedWindow("RePlay",1); IplImage * gray_image= cvCreateImage(cvGetSize(show),8,1); cvCvtColor(show,gray_image,CV_BGR2GRAY); cout<<"获取源图像灰度图过程完成... "; cvFindCornerSubPix(gray_image,image_points_buf,count,cvSize(11,11),cvSize(-1,-1), cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,0.1)); cout<<"灰度图亚像素化过程完成... "; cvDrawChessboardCorners(show,board_size,image_points_buf,count,found); cout<<"在源图像上绘制角点过程完成... "; cvShowImage("RePlay",show); cvWaitKey(0); } if(total_per_image==count){ step=successes*total_per_image; //计算存储相应坐标数据的步长 for(int i=step,j=0;j<total_per_image;++i,++j){ CV_MAT_ELEM(*image_points,float,i,0)=image_points_buf[j].x; CV_MAT_ELEM(*image_points,float,i,1)=image_points_buf[j].y; CV_MAT_ELEM(*object_points,float,i,0)=(float)((j/board_width)*square_length); CV_MAT_ELEM(*object_points,float,i,1)=(float)((j%board_width)*square_height); CV_MAT_ELEM(*object_points,float,i,2)=0.0f; } CV_MAT_ELEM(*point_counts,int,successes,0)=total_per_image; successes++; } a++; } cvReleaseImage(&show); cvDestroyWindow("RePlay"); cout<<"********************************************* "; cout<<number_image<<"帧图片中，标定成功的图片为"<<successes<<"帧... "; cout<<number_image<<"帧图片中，标定失败的图片为"<<number_image-successes<<"帧... "; cout<<"********************************************* "; cout<<"按任意键开始计算摄像机内参数... "; CvCapture* capture1; capture1=cvCreateCameraCapture(0); IplImage * show_colie; show_colie=cvQueryFrame(capture1); CvMat * object_points2=cvCreateMat(successes*total_per_image,3,CV_32FC1); CvMat * image_points2=cvCreateMat(successes*total_per_image,2,CV_32FC1); CvMat * point_counts2=cvCreateMat(successes,1,CV_32SC1); for(int i=0;i<successes*total_per_image;++i){ CV_MAT_ELEM(*image_points2,float,i,0)=CV_MAT_ELEM(*image_points,float,i,0); CV_MAT_ELEM(*image_points2,float,i,1)=CV_MAT_ELEM(*image_points,float,i,1); CV_MAT_ELEM(*object_points2,float,i,0)=CV_MAT_ELEM(*object_points,float,i,0); CV_MAT_ELEM(*object_points2,float,i,1)=CV_MAT_ELEM(*object_points,float,i,1); CV_MAT_ELEM(*object_points2,float,i,2)=CV_MAT_ELEM(*object_points,float,i,2); } for(int i=0;i<successes;++i){ CV_MAT_ELEM(*point_counts2,int,i,0)=CV_MAT_ELEM(*point_counts,int,i,0); } cvReleaseMat(&object_points); cvReleaseMat(&image_points); cvReleaseMat(&point_counts); //初始化相机内参矩阵 CV_MAT_ELEM(*intrinsic_matrix,float,0,0)=1.0f; CV_MAT_ELEM(*intrinsic_matrix,float,1,1)=1.0f; //标定相机的内参矩阵和畸变系数向量 cvCalibrateCamera2(object_points2,image_points2,point_counts2,cvGetSize(show_colie), intrinsic_matrix,distortion_coeffs,NULL,NULL,0); cout<<"摄像机内参数矩阵为： "; cout<<CV_MAT_ELEM(*intrinsic_matrix,float,0,0)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,0,1) <<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,0,2) <<" "; cout<<CV_MAT_ELEM(*intrinsic_matrix,float,1,0)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,1,1) <<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,1,2) <<" "; cout<<CV_MAT_ELEM(*intrinsic_matrix,float,2,0)<<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,2,1) <<" "<<CV_MAT_ELEM(*intrinsic_matrix,float,2,2) <<" "; cout<<"畸变系数矩阵为： "; cout<<CV_MAT_ELEM(*distortion_coeffs,float,0,0)<<" "<<CV_MAT_ELEM(*distortion_coeffs,float,1,0) <<" "<<CV_MAT_ELEM(*distortion_coeffs,float,2,0) <<" "<<CV_MAT_ELEM(*distortion_coeffs,float,3,0) <<" "<<CV_MAT_ELEM(*distortion_coeffs,float,4,0) <<" "; cvSave("Intrinsics.xml",intrinsic_matrix); cvSave("Distortion.xml",distortion_coeffs); cout<<"摄像机矩阵、畸变系数向量已经分别存储在名为Intrinsics.xml、Distortion.xml文档中 "; CvMat * intrinsic=(CvMat *)cvLoad("Intrinsics.xml"); CvMat * distortion=(CvMat *)cvLoad("Distortion.xml"); IplImage * mapx=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,1); IplImage * mapy=cvCreateImage(cvGetSize(show_colie),IPL_DEPTH_32F,1); cvInitUndistortMap(intrinsic,distortion,mapx,mapy); cvNamedWindow("原始图像",1); cvNamedWindow("非畸变图像",1); cout<<"按‘E’键退出显示... "; while(show_colie){ IplImage * clone=cvCloneImage(show_colie); cvShowImage("原始图像",show_colie); cvRemap(clone,show_colie,mapx,mapy); cvReleaseImage(&clone); cvShowImage("非畸变图像",show_colie); if(cvWaitKey(10)=='e'){ break; } show_colie=cvQueryFrame(capture1); } return 0; }
