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长度单位毫米
看到本文被转载很多次很高兴但是之前的代码有点小问题且不易懂。于是乎写了一个简洁的代码
首先介绍用本程序标定的步骤：
1,。拍完图片之后将图片重命名为下图所示形式
2.将照片放在程序的cam文件夹下
3.然后运行程序，按照提示输入信息
4.最后在output文件夹找到result_data_no_optim.txt
代码如下：
//author:YeahPingYE
//function:auto calibration
//time:2014/11/25
//
//
#include<highgui.h>
#include<cv.h>
#include<iostream>
#include<fstream>
using namespace std;
void save_result(CvMat*cam_rotation_all, CvMat*cam_translation_vector_all,
CvMat*cam_intrinsic_matrix, CvMat*cam_distortion_coeffs,char*pathc,int sucesses);
int main()
{
/*initialation
//input:the number of images......num_image
// prj_board_w,prj_board_h
// cam_board_w,cam_board_h
*/
CvMat*cam_object_points2;
CvMat*cam_image_points2;
int cam_board_n;
int successes = 0;
int img_num, cam_board_w, cam_board_h,cam_Dx,cam_Dy;
cout << "输入的图像的组数\n";
cin >> img_num;
cout << "输入**真实**棋盘格的##横轴##方向的角点个数\n";
cin >> cam_board_w;
cout << "输入**真实**棋盘格的##纵轴##方向的角点个数\n";
cin >> cam_board_h;
cout << "输入**真实**棋盘格的##横轴##方向的长度\n";
cin >> cam_Dx;
cout << "输入**真实**棋盘格的##纵轴##方向的长度\n";
cin >> cam_Dy;
cam_board_n = cam_board_w*cam_board_h;
/*
//init
//
//
*/
//camera init
CvSize cam_board_sz = cvSize(cam_board_w, cam_board_h);
CvMat*cam_image_points = cvCreateMat(cam_board_n*(img_num), 2, CV_32FC1);
CvMat*cam_object_points = cvCreateMat(cam_board_n*(img_num), 3, CV_32FC1);
CvMat*cam_point_counts = cvCreateMat((img_num), 1, CV_32SC1);
CvPoint2D32f*cam_corners = new CvPoint2D32f[cam_board_n];
int cam_corner_count;
int cam_step;
CvMat*cam_intrinsic_matrix = cvCreateMat(3, 3, CV_32FC1);
CvMat*cam_distortion_coeffs = cvCreateMat(4, 1, CV_32FC1);
CvSize cam_image_sz;
//window intit
cvNamedWindow("window", 0);
//get image size
IplImage *cam_image_temp = cvLoadImage("..\\cam\\cam1.bmp", 0);
cam_image_sz = cvGetSize(cam_image_temp);
char failurebuf[20] = { 0 };
/*
//extract cornner
// camera image
//
// pattern
*/
/*
//extrat the cam cornner
//
//
//
*/
fstream cam_data;
cam_data.open("..\\output\\TXT\\cam_corners.txt", ofstream::out);
fstream cam_object_data;
cam_object_data.open("..\\output\\TXT\\cam_object_data.txt", ofstream::out);
//process the prj image so that we can easy find cornner
for (int ii = 1; ii < img_num + 1; ii++)
{
char cambuf[20] = { 0 };
sprintf(cambuf, "..\\cam\\cam%d.bmp", ii);
IplImage *cam_image = cvLoadImage(cambuf, 0);
//extract cam cornner
int cam_found = cvFindChessboardCorners(cam_image, cam_board_sz, cam_corners, &cam_corner_count,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FILTER_QUADS);
cvFindCornerSubPix(cam_image, cam_corners, cam_corner_count,
cvSize(11, 11), cvSize(-1, -1), cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
cvDrawChessboardCorners(cam_image, cam_board_sz, cam_corners, cam_corner_count, cam_found);
if (cam_corner_count != cam_board_n)
cout << "find cam"<<ii<<" corner failed!\n";
//when cam and prj are success store the result
if ( cam_corner_count == cam_board_n) {
//store cam result
cam_step = successes*cam_board_n;
for (int i = cam_step, j = 0; j < cam_board_n; ++i, ++j) {
CV_MAT_ELEM(*cam_image_points, float, i, 0) = cam_corners[j].x;
CV_MAT_ELEM(*cam_image_points, float, i, 1) = cam_corners[j].y;
CV_MAT_ELEM(*cam_object_points, float, i, 0) = (j/cam_board_w)*cam_Dx;
CV_MAT_ELEM(*cam_object_points, float, i, 1) = (j % cam_board_w)*cam_Dy;
CV_MAT_ELEM(*cam_object_points, float, i, 2) = 0.0f;
cam_data << cam_corners[j].x << "\t" << cam_corners[j].y << "\n";
cam_object_data << (j/cam_board_w)*cam_Dx << "\t" << (j %cam_board_w)*cam_Dy << "\t0\n";
}
CV_MAT_ELEM(*cam_point_counts, int, successes, 0) = cam_board_n;
successes++;
cout << "success number" << successes << endl;
cvShowImage("window", cam_image);
cvWaitKey(500);
}
}
if (successes < 2)
exit(0);
/*
//restore the success point
*/
//cam
cam_image_points2 = cvCreateMat(cam_board_n*(successes), 2, CV_32FC1);
cam_object_points2 = cvCreateMat(cam_board_n*(successes), 3, CV_32FC1);
CvMat*cam_point_counts2 = cvCreateMat((successes), 1, CV_32SC1);
for (int i = 0; i < successes*cam_board_n; ++i){
CV_MAT_ELEM(*cam_image_points2, float, i, 0) = CV_MAT_ELEM(*cam_image_points, float, i, 0);
CV_MAT_ELEM(*cam_image_points2, float, i, 1) = CV_MAT_ELEM(*cam_image_points, float, i, 1);
CV_MAT_ELEM(*cam_object_points2, float, i, 0) = CV_MAT_ELEM(*cam_object_points, float, i, 0);
CV_MAT_ELEM(*cam_object_points2, float, i, 1) = CV_MAT_ELEM(*cam_object_points, float, i, 1);
CV_MAT_ELEM(*cam_object_points2, float, i, 2) = CV_MAT_ELEM(*cam_object_points, float, i, 2);
}
for (int i = 0; i < successes; ++i){
CV_MAT_ELEM(*cam_point_counts2, int, i, 0) = CV_MAT_ELEM(*cam_point_counts, int, i, 0);
}
cvSave("..\\output\\XML\\cam_corners.xml", cam_image_points2);
cvReleaseMat(&cam_object_points);
cvReleaseMat(&cam_image_points);
cvReleaseMat(&cam_point_counts);
/*
//calibration for camera
//
*/
//calib for cam
CV_MAT_ELEM(*cam_intrinsic_matrix, float, 0, 0) = 1.0f;
CV_MAT_ELEM(*cam_intrinsic_matrix, float, 1, 1) = 1.0f;
CvMat* cam_rotation_all = cvCreateMat( successes, 3, CV_32FC1);
CvMat* cam_translation_vector_all = cvCreateMat( successes,3, CV_32FC1);
cvCalibrateCamera2(
cam_object_points2,
cam_image_points2,
cam_point_counts2,
cam_image_sz,
cam_intrinsic_matrix,
cam_distortion_coeffs,
cam_rotation_all,
cam_translation_vector_all,
0//CV_CALIB_FIX_ASPECT_RATIO
);
cvSave("..\\output\\XML\\cam_intrinsic_matrix.xml", cam_intrinsic_matrix);
cvSave("..\\output\\XML\\cam_distortion_coeffs.xml", cam_distortion_coeffs);
//calib
cvSave("..\\output\\XML\\cam_rotation_all.xml", cam_rotation_all);
cvSave("..\\output\\XML\\cam_translation_vector_all.xml", cam_translation_vector_all);
char path1[100] = "..\\output\\result_data_no_optim.txt";
save_result(cam_rotation_all, cam_translation_vector_all,
cam_intrinsic_matrix, cam_distortion_coeffs,path1,successes);
}
void save_result(CvMat*cam_rotation_all, CvMat*cam_translation_vector_all,
CvMat*cam_intrinsic_matrix, CvMat*cam_distortion_coeffs,char*pathc,int sucesses)
{
fstream Yeah_result;
Yeah_result.open(pathc, ofstream::out);
Yeah_result << setprecision(12) << "fc[0] =" << CV_MAT_ELEM(*cam_intrinsic_matrix, float, 0, 0
) << "; fc[1] =" << CV_MAT_ELEM(*cam_intrinsic_matrix, float, 1, 1) << "; //CAM的焦距\n";
Yeah_result << setprecision(12) << "cc[0] = " << CV_MAT_ELEM(*cam_intrinsic_matrix, float, 0, 2)
<< "; cc[1] = " << CV_MAT_ELEM(*cam_intrinsic_matrix, float, 1, 2) << ";//CAM中心点\n";
Yeah_result << setprecision(12) << "kc[0] =" << CV_MAT_ELEM(*cam_distortion_coeffs, float, 0, 0) <<
"; kc[1] =" << CV_MAT_ELEM(*cam_distortion_coeffs, float, 1, 0) <<
"; kc[2] =" << CV_MAT_ELEM(*cam_distortion_coeffs, float, 2, 0) <<
"; kc[3] =" << CV_MAT_ELEM(*cam_distortion_coeffs, float, 3, 0)
<< "; kc[4] =0;//畸变参数，请参照MATLAB里的定义\n\n外参数:\n";
for(int i=0;i<sucesses;++i)
{
Yeah_result<<"r:("<<setprecision(12) <<CV_MAT_ELEM(*cam_rotation_all, float, i, 0)<<"\t,"<<CV_MAT_ELEM(*cam_rotation_all, float, i, 1)<<"\t,"<<CV_MAT_ELEM(*cam_rotation_all, float, i, 2)<<")\n";
Yeah_result<<"t:("<<setprecision(12) <<CV_MAT_ELEM(*cam_translation_vector_all, float, i, 0)<<"\t,"<<CV_MAT_ELEM(*cam_translation_vector_all, float, i, 1)<<"\t,"<<CV_MAT_ELEM(*cam_translation_vector_all, float, i, 2)<<")\n\n\n";
}
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来源：CSDN
作者：zhouyelihua
链接：https://blog.csdn.net/zhouyelihua/article/details/38421377