毕业设计过程记录五，单目摄像机标定

工作上事情太多了只有一小部分时间完成毕业设计，标定工作拖了将近一个月才做完，不过这次的代码是直接使用别人完成的，有点遗憾！

话不多说上代码！

#include <string>  #include <iostream>  #include <cv.h>  #include <highgui.h>    //#pragma comment(lib, "ml.lib")  //#pragma comment(lib, "cv.lib")  //#pragma comment(lib, "cvaux.lib")  //#pragma comment(lib, "cvcam.lib")  //#pragma comment(lib, "cxcore.lib")  //#pragma comment(lib, "cxts.lib")  //#pragma comment(lib, "highgui.lib")  //#pragma comment(lib, "cvhaartraining.lib")    using namespace std;    int main()  {      int cube_length=7;        CvCapture* capture;        capture=cvCreateCameraCapture(0);        if(capture==0)      {          printf("无法捕获摄像头设备！\n\n");          return 0;      }      else      {          printf("捕获摄像头设备成功！！\n\n");      }        IplImage* frame = NULL;        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...\n按“Q”键退出截取帧过程...\n\n");        int number_image=1;      char *str1;      str1=".jpg";      char filename[20]="";        while(true)      {          frame=cvQueryFrame(capture);          if(!frame)              break;          cvShowImage("摄像机帧截取窗口",frame);            if(cvWaitKey(10)=='c')          {              sprintf_s (filename,"%d.jpg",number_image);              cvSaveImage(filename,frame);              cout<<"成功获取当前帧，并以文件名"<<filename<<"保存...\n\n";              printf("按“C”键截取当前帧并保存为标定图片...\n按“Q”键退出截取帧过程...\n\n");              number_image++;          }          else if(cvWaitKey(10)=='q')          {              printf("截取图像帧过程完成...\n\n");              cout<<"共成功截取"<<--number_image<<"帧图像！！\n\n";              break;          }      }        cvReleaseImage(&frame);      cvDestroyWindow("摄像机帧截取窗口");        IplImage * show;      cvNamedWindow("RePlay",1);        int a=1;      int number_image_copy = number_image;        CvSize board_size=cvSize(7,7);      int board_width=board_size.width;      int board_height=board_size.height;      int total_per_image=board_width*board_height;      CvPoint2D32f * image_points_buf = new CvPoint2D32f[total_per_image];      CvMat * image_points=cvCreateMat(number_image*total_per_image,2,CV_32FC1);      CvMat * object_points=cvCreateMat(number_image*total_per_image,3,CV_32FC1);      CvMat * point_counts=cvCreateMat(number_image,1,CV_32SC1);      CvMat * intrinsic_matrix=cvCreateMat(3,3,CV_32FC1);      CvMat * distortion_coeffs=cvCreateMat(5,1,CV_32FC1);        int count;      int found;      int step;      int successes=0;        while(a<=number_image_copy)      {          sprintf_s (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)          {                     cout<<"第"<<a<<"帧图片无法找到棋盘格所有角点!\n\n";              cvNamedWindow("RePlay",1);              cvShowImage("RePlay",show);              cvWaitKey(0);            }          else          {              cout<<"第"<<a<<"帧图像成功获得"<<count<<"个角点...\n";                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...\n";              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...\n";              cvDrawChessboardCorners(show,board_size,image_points_buf,count,found);              cout<<"在源图像上绘制角点过程完成...\n\n";              cvShowImage("RePlay",show);                cvWaitKey(0);          }            if(total_per_image==count)          {              step=successes*total_per_image;              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/cube_length);                  CV_MAT_ELEM(*object_points,float,i,1)=(float)(j%cube_length);                  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<<"*********************************************\n";      cout<<number_image<<"帧图片中，标定成功的图片为"<<successes<<"帧...\n";      cout<<number_image<<"帧图片中，标定失败的图片为"<<number_image-successes<<"帧...\n\n";      cout<<"*********************************************\n\n";        cout<<"按任意键开始计算摄像机内参数...\n\n";        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);        CV_MAT_ELEM(*intrinsic_matrix,float,0,0)=1.0f;      CV_MAT_ELEM(*intrinsic_matrix,float,1,1)=1.0f;        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：\n";      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)          <<"\n\n";      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)          <<"\n\n";      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)          <<"\n\n";        cout<<"畸变系数矩阵为：\n";      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)          <<"\n\n";        cvSave("D:\\摄像机矩阵.xml",intrinsic_matrix);      cvSave("D:\\畸变系数向量.xml",distortion_coeffs);        cout<<"摄像机矩阵、畸变系数向量已经分别存储在名为摄像机矩阵.xml、畸变系数向量.xml文档中\n\n";        CvMat * intrinsic=(CvMat *)cvLoad("D:\\摄像机矩阵.xml");      CvMat * distortion=(CvMat *)cvLoad("D:\\畸变系数向量.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...\n\n";        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;  }  

使用方法，按c键截图，多截几幅图。然后按q键进行识别，截了几张图按几次q，他要对每张图进行分析标定，最后分析完它自动计算矩阵和畸变系数。

摄像机标定是 为了要得到矩阵和畸变系数，这样才能在测距时，输入这些参数然后矫正，消除误差。

下一次在搞定平面测距之后再发。