opencv標定程序（改動）
阿新 • • 發佈：2017-06-27
dsm camera boa center create auth src targe 照片
轉載請註明來自：http://blog.csdn.net/zhouyelihua/article/details/38421377
資源下載見：點擊打開鏈接
百度雲盤免積分下載：https://pan.baidu.com/s/1bzy20u
有關於標定的基本原理詳見點擊打開鏈接
看到本文被轉載非常多次非常高興可是之前的代碼有點小問題且不易懂。於是乎寫了一個簡潔的代碼
首先介紹用本程序標定的步驟：
1,。
拍完圖片之後將圖片重命名為下圖所看到的形式
2.將照片放在程序的cam目錄下
3.然後執行程序。依照提示輸入信息
4.最後在output目錄找到result_data_no_optim.txt
代碼例如以下：
//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 << "輸入的圖像的組數\n";
cin >> img_num;
cout << "輸入**真實**棋盤格的##橫軸##方向的角點個數\n";
cin >> cam_board_w;
cout << "輸入**真實**棋盤格的##縱軸##方向的角點個數\n";
cin >> cam_board_h;
cout << "輸入**真實**棋盤格的##橫軸##方向的長度\n";
cin >> cam_Dx;
cout << "輸入**真實**棋盤格的##縱軸##方向的長度\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中心點\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;//畸變參數，請參照MATLAB裏的定義\n\n外參數:\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";
}
}
假設您認為此博客對您實用，歡迎對我進行小額贊助
不籌錢娶媳婦的程序猿不是好程序猿。
opencv標定程序（改動）