1、#include cvut.h#include #include #include using namespace cvut;using namespace std;#pragma comment(lib,cxcore.lib)#pragma comment(lib,cv.lib)#pragma comment(lib,highgui.lib)void main() ifstream fin(calibdata.txt); /*定標所用圖像文件的路徑*/ofstream fout(caliberation_result.txt); /* 保存定標結果的文件 */讀取每一幅圖像，從中提取出角點，

2、然后對角點進行亞像素精確化cout開始提取角點；int image_count=0; /* 圖像數量 */CvSize image_size; /* 圖像的尺寸 */CvSize board_size = cvSize(5,7); /* 定標板上每行、列的角點數 */CvPoint2D32f*image_points_buf=newCvPoint2D32fboard_size.width*board_size.height; /* 緩存每幅圖像上檢測到的角點 */Seq image_points_seq; /* 保存檢測到的所有角點 */ string filename; while (get

3、line(fin,filename) image_count+; int count;Image view(filename); if (image_count = 1) image_size.width = view.size().width; image_size.height = view.size().height;/*提取角點*/if (0 = cvFindChessboardCorners( view.cvimage, board_size, image_points_buf, &count, CV_CALIB_CB_ADAPTIVE_THRESH ) coutcan not fi

4、nd chessboard corners!n;exit(1); else Image view_gray(view.size(),8,1); rgb2gray(view,view_gray);/*亞像素精確化*/ cvFindCornerSubPix( view_gray.cvimage, image_points_buf, count, cvSize(11,11), cvSize(-1,-1), cvTermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 30, 0.1 )； image_points_seq.push_back(image_poin

5、ts_buf,count);/*在圖像上顯示角點位置*/ cvDrawChessboardCorners( view.cvimage, board_size, image_points_buf, count, 1);view.show(calib); cvWaitKey(); view.close(); delete image_points_buf; cout角點提取完成！ n;攝像機定標cout開始定標;CvSize square_size = cvSize(10,10); /*實際測量得到的定標板上每個棋盤格的大小*/Matrix object_points(1,board_size.w

6、idth*board_size.height*image_count,3); /*保存定標板上角點的三維坐標*/Matrix image_points(1,image_points_seq.cvseq-total,2); /*保存提取的所有 角點 */Matrix point_counts(1,image_count,1); /* 每幅圖像中角點的數量 */Matrix intrinsic_matrix(3,3,1); /* 攝像機內參數矩陣 */Matrix distortion_coeffs(1,4,1); /* 攝像機的 4 個畸變系數：k1,k2,p1,p2 */Matrix rota

7、tion_vectors(1,image_count,3); /* 每幅圖像的旋轉向量 */Matrix translation_vectors(1,image_count,3); /* 每幅圖像的平移向量 */*初始化定標板上角點的三維坐標*/int i,j,t;for (t=0;timage_count;t+) for (i=0;iboard_size.height;i+) for (j=0;jboard_size.width;j+) /*假設定標板放在世界坐標系中z=0的平面上*/object_points(0,t*board_size.height*board_size.width+i

8、*board_size.width+j,0) i*square_size.width;object_points(0,t*board_size.height*board_size.width+i*board_size.width+j,1) j*square_size.height;object_points(0,t*board_size.height*board_size.width+i*board_size.width+j,2) 0;/*將角點的存儲結構轉換成矩陣形式*/for (i=0;itotal;i+) image_points(0,i,0) = image_points_seqi.x

9、;image_points(0,i,1) = image_points_seqi.y;/*初始化每幅圖像中的角點數量，這里我們假設每幅圖像中都可以看到完整的定標板*/for (i=0;iimage_count;i+)point_counts(0,i) = board_size.width*board_size.height;/*開始定標*/cvCalibrateCamera2(object_points.cvmat,image_points.cvmat,point_counts.cvmat,image_size,intrinsic_matrix.cvmat,distortion_coeffs.

10、cvmat,rotation_vectors.cvmat,translation_vectors.cvmat,0);cout定標完成！ n;對定標結果進行評價cout開始評價定標結果n;double total_err = 0.0; /*所有圖像的平均誤差的總和*/double err = 0.0; /*每幅圖像的平均誤差*/Matrix image_points2(1,point_counts(0,0,0),2); /* 保存重新計算得到的投影點 */coutt每幅圖像的定標誤差：n;fout每幅圖像的定標誤差：n;for (i=0;iimage_count;i+) /*通過得到的攝像機內外

11、參數，對空間的三維點進行重新投影計算，得到新的投影點*/cvProjectPoints2(object_points.get_cols(i*point_counts(0,0,0),(i+1)*point_counts(0,0,0)-1).cvmat,rotation_vectors.get_col(i).cvmat,translation_vectors.get_col(i).cvmat, intrinsic_matrix.cvmat, distortion_coeffs.cvmat, image_points2.cvmat, 0,0,0,0);/*計算新的投影點和舊的投影點之間的誤差*/er

12、rcvNorm(image_points.get_cols(i*point_counts(0,0,0),(i+1)*point_counts(0,0,0)-1).cvm at,image_points2.cvmat, CV_L1);total_err += err/=point_counts(0,0,0);couttt 第i+1幅圖像的平均誤差:err像素n;foutt 第i+1幅圖像的平均誤差：err像素n;coutt 總體平均誤差：total_err/image_count像素n;fout總體平均誤差：total_err/image_count像素nn;cout評價完成！ n;保存定標結果

13、cout開始保存定標結果;Matrix rotation_vector(3,1); /* 保存每幅圖像的旋轉向量 */Matrix rotation_matrix(3,3); /* 保存每幅圖像的旋轉矩陣 */fout相機內參數矩陣：n;foutintrinsic_matrixn;fout畸變系數：n;foutdistortion_coeffsn;for (i=0;iimage_count;i+) fout”第i+1幅圖像的旋轉向量：n;foutrotation_vectors.get_col(i);/*對旋轉向量進行存儲格式轉換*/for (j=0;j3;j+) rotation_vector(j,0,0) = rota