利用opencv进行相机标定程序

 #include "Stafx.h"

 ;   //棋盘上有13个格子，那么角点的数目12
 ;
 ;  //图片的总张数
 int main(int argc, char** argv)
 {
     ;
     int board_n=board_h*board_w;  //一张图像上，角点的数目
     CvSize board_sz=cvSize(board_w,board_h);
     CvMat* object_points=cvCreateMat(image_count*board_n,,CV_32FC1);  //实际坐标系（以棋盘左上角第一个角点为坐标原点），角点的坐标，单位是方块
     CvMat* image_points=cvCreateMat(image_count*board_n,,CV_32FC1);   //在图像上找到角点的坐标,坐标原点图像左上角，单位像素
     CvMat* point_counts=cvCreateMat(board_n,,CV_32SC1);    //每个图像上角点个数

     ;    //累计图像上所有角点被找到图像的张数
     while (count++<image_count)
     {
         std::string filename="E:\\软件学习\\LearningOpenCV_Code\\calibration\\";
         ];
         itoa(count,str,);//转换为字符串
         std::string str1;
         int length=strlen(str);
         *(str+length)='.';
         *(str+length+)='j';
         *(str+length+)='p';
         *(str+length+)='g';
         *(str+length+)='\0';
         str1=str;
         filename+=str1;
         IplImage* src=cvLoadImage(filename.c_str(),CV_LOAD_IMAGE_UNCHANGED);
         IplImage* gray=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,);
         cvCvtColor(src,gray,CV_RGB2GRAY);
         CvPoint2D32f* corners=new CvPoint2D32f[board_n];  //一张图像上角点的坐标
         int corner_count;     //一张图像上角点的数目
         int found=cvFindChessboardCorners(src,board_sz,corners,&corner_count,
                                 CV_CALIB_CB_ADAPTIVE_THRESH|CV_CALIB_CB_FILTER_QUADS);//找到棋盘的角点,如果所有角点找到返回1，否则返回0，这里指的是所有的角点

         cvFindCornerSubPix(gray, corners, corner_count, cvSize(,),cvSize(-,-),
                             cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,, 0.1)); //寻找亚素点,gray一定要是8位单通道的图像
         cvDrawChessboardCorners(src,board_sz,corners,corner_count,found);             //将角点画出，src一定要是彩色图像
         //cvShowImage("1",src);
         //cvWaitKey();
         if (corner_count==board_n)  //一张图像上所有角点被找到
         {
             int step=a*board_n;  //第k幅角点全部找到图像上角点的存储的起始地址
             ;
             for (int i=step;j<corner_count;i++,j++)
             {
                 CV_MAT_ELEM(*object_points,)=j/board_w;  //角点的横坐标，单位不是像素，而是以棋盘上每个方块为一个单位
                 CV_MAT_ELEM(*object_points,)=j%board_w;  //角点的纵坐标，每个方块为一个单位
                 CV_MAT_ELEM(*object_points,)=;      //齐次坐标,表示点
                 CV_MAT_ELEM(*image_points,)=corners[j].x; //图像坐标系的坐标
                 CV_MAT_ELEM(*image_points,)=corners[j].y;
             };
             CV_MAT_ELEM(*point_counts,)=board_n;
             a++;
         }
     }
     //由于图像中存在所有角点未找到的情况，所以上面object_points的空间未存满，需要重新定义
     CvMat* object_points2=cvCreateMat(a*board_n,,CV_32FC1);
     CvMat* image_points2=cvCreateMat(a*board_n,,CV_32FC1);
     CvMat* point_counts2=cvCreateMat(a,,CV_32SC1);
     CvMat* intrinsic_matrix=cvCreateMat(,,CV_32FC1);   //相机内参数矩阵
     CvMat* distortion_coeffs=cvCreateMat(,,CV_32FC1);  //畸变系数矩阵
     CvMat* rotation_vector=cvCreateMat(a,,CV_32FC1);    //旋转矩阵
     CvMat* translation_vector=cvCreateMat(a,,CV_32FC1);  //平移矩阵
     ;i<a*board_n;i++)
     {
         CV_MAT_ELEM(*object_points2,)=CV_MAT_ELEM(*object_points,);
         CV_MAT_ELEM(*object_points2,)=CV_MAT_ELEM(*object_points,);
         CV_MAT_ELEM(*object_points2,)=;
         CV_MAT_ELEM(*image_points2,)=CV_MAT_ELEM(*image_points,);
         CV_MAT_ELEM(*image_points2,)=CV_MAT_ELEM(*image_points,);
     }
     ;i<a;i++)
         CV_MAT_ELEM(*point_counts2,)=CV_MAT_ELEM(*point_counts,);
     cvReleaseMat(&object_points);
     cvReleaseMat(&image_points);
     cvReleaseMat(&point_counts);
     //内置参数矩阵设置,初始化
     CV_MAT_ELEM(*intrinsic_matrix,,)=1.0;
     CV_MAT_ELEM(*intrinsic_matrix,,)=1.0;
     //校正相机参数,cvSize(1600,1200)为输入图像的真实长度和宽度，单位为像素
     cvCalibrateCamera2(object_points2,image_points2,point_counts2,cvSize(,),
                             intrinsic_matrix,distortion_coeffs,rotation_vector,translation_vector,CV_CALIB_FIX_ASPECT_RATIO);
     //图像校正
     IplImage* mapx=cvCreateImage(cvSize(,),IPL_DEPTH_32F,);
     IplImage* mapy=cvCreateImage(cvSize(,),IPL_DEPTH_32F,);
     cvInitUndistortMap(intrinsic_matrix,distortion_coeffs,mapx,mapy);
     IplImage* test_image=cvLoadImage("E:\\软件学习\\LearningOpenCV_Code\\calibration\\22.jpg",CV_LOAD_IMAGE_UNCHANGED);
     if (!test_image)
     {
         std::cout<<"error"<<std::endl;
     }
     cvShowImage("原图像",test_image);
     IplImage* t=cvCloneImage(test_image);
     cvRemap(t,test_image,mapx,mapy);
     cvShowImage("校正后图像",test_image);
     cvWaitKey();
     ;
 }

测试图片：opencv课后习题答案中LearningOpencv_Code中calibration文件中的图片