摄像机标定用于机械臂抓举等（利用标定将图像上的点映射为三维坐标）

               在实验室或者是工程上，我们常常需要将拍摄到的图像的二维图像坐标来计算三维坐标。

  

       如上图所示，我们有上图这样的一副图片。我们需要将物体和机械臂的三维位置算出来，使得机械臂能够精确的抓住物体。

       我们采用张正友标定的方法标定出内外参数，利用其内参与外参数算出其对应的三维坐标。具体公式略！可以参考张PAMI的论文。

     

/*/
//author:YeahPingYE
//function:
//time:2014/11/25
//
//
//
//
//
//*/
#include
#include
#include
#include
using namespace std;

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;
	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;
	double cam_Dx = 30;//chessboard's width
	double cam_Dy = 30;
	cout << "输入**真实**棋盘格的##横轴##大小dx\n";
	cin >> cam_Dx;
	cout << "输入**真实**棋盘格的##纵轴##大小dy\n";
	cin >> cam_Dy;
	/*int img_num =4;
	int cam_board_w = 10;
	int cam_board_h = 8;*/
	cam_board_n = cam_board_w*cam_board_h;
	double x_pixel, y_pixel;
	cout << "输入要求的位置的像素坐标\n横轴方向的像素坐标#u#\n";
	cin >> x_pixel;
	cout << "纵轴方向的像素坐标#v#\n";
	cin >> y_pixel;
	//x_pixel =0;
	//y_pixel = 0;
	//x_pixel = 6.01938965e+002;
	//y_pixel = 5.65429077e+002;
	//x_pixel = 7.04663452e+002;
	//y_pixel = 5.54746582e+002;
	//x_pixel = 8.88867798e+002;
	//y_pixel = 9.58109802e+002;
	
	 
	/*
	//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);

	/*
	//extract cornner
	// camera image
	
	*/



	
	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);

		//when camare 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;
			}
			CV_MAT_ELEM(*cam_point_counts, int, successes, 0) = cam_board_n;




			successes++;
			cout << "success number" << successes << endl;
			cvShowImage("window", cam_image);
			cvWaitKey(500);
		}

	}

	/*
	//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);
	cvSave("..\\output\\XML\\cam_rotation_all.xml", cam_rotation_all);
	cvSave("..\\output\\XML\\cam_translation_vector_all.xml", cam_translation_vector_all);
	
	CvMat* cam_dist_image_points = cvCreateMat(cam_board_n, 1, CV_32FC2);
	CvMat* cam_undist_image_points = cvCreateMat(cam_board_n, 1, CV_32FC2);
	for (int j = 0; j < cam_board_n; ++j)
	{
		cvSet1D(cam_dist_image_points, j,
			cvScalar(CV_MAT_ELEM(*cam_image_points2, float, j, 0),
			CV_MAT_ELEM(*cam_image_points2, float,  j, 1)));
		
		//cout << CV_MAT_ELEM(*cam_dist_image_points, float, j, 0) << "\t" << CV_MAT_ELEM(*cam_dist_image_points, float, j, 1) << endl;
	}
		cvUndistortPoints(cam_dist_image_points, cam_undist_image_points,
		cam_intrinsic_matrix, cam_distortion_coeffs, NULL, NULL);
	cvReleaseMat(&cam_dist_image_points);
	CvMat* homography = cvCreateMat(3, 3, CV_32FC1);
	CvMat* cam_src = cvCreateMat(cam_board_n, 3, CV_32FC1);
	CvMat* cam_dst = cvCreateMat(cam_board_n, 3, CV_32FC1);
	for (int j = 0; j

上述中像素（969.449,635.648）对应的真实第一个棋盘格的坐标是（90,60,0）上图得到的结果误差比较小。

具体程序的操作步骤及相关文件见网址（vs2013配置了opencv可以直接运行）：

http://download.csdn.net/download/zhouyelihua/8236557

click here

csdn的下载这个版块实在太差了：要下载的上百度云盘http://pan.baidu.com/s/1hefQe

点击打开链接