opencv标定程序（改动）

转载请注明来自：http://blog.csdn.net/zhouyelihua/article/details/38421377

资源下载见：点击打开链接

百度云盘免积分下载：https://pan.baidu.com/s/1bzy20u

有关于标定的基本原理详见点击打开链接

看到本文被转载非常多次非常高兴可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看到的形式

2.将照片放在程序的cam目录下

3.然后执行程序。依照提示输入信息

4.最后在output目录找到result_data_no_optim.txt

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代码例如以下：

//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 << "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;//畸变參数，请參照MATLAB里的定义\n\n外參数:\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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