基于OpnecCV的鱼眼镜头校正

UINT CFisheyeCorrectionDlg::StartLineAcq(LPVOID lpParam)
{
    ofstream fout("caliberation_result.txt");  /**  保存定标结果的文件     **/
    /**********************************************************************  
    读取每一幅图像，从中提取出角点，然后对角点进行亚像素精确化  
    *********************************************************************/   
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("开始提取角点…"));

    int image_count=36;                    /****    图像数量     ****/  
    bool bImageFindCorner[36]={false};       //对应图像是否找到角点
    //Size board_size = Size(26,26);          /****    定标板上每行、列的角点数       ****/  
    Size board_size = Size(8,8);          /****    定标板上每行、列的角点数       ****/ 
    vector<Point2f> corners;                /****    缓存每幅图像上检测到的角点       ****/
    vector<vector<Point2f>>  corners_Seq;   /****    保存检测到的所有角点       ****/   
    vector<Mat>  image_Seq;
    int successImageNum = 0;                /****    成功提取角点的棋盘图数量   ****/


    int count = 0;
    for( int i = 0;  i != image_count ; i++)
    {

        char ch_sf[20];
        itoa(i+1,ch_sf,10);
        string s_status;
        s_status=s_status+"正在提取第"+ch_sf+"张图角点...";
        CString C_Status;
        C_Status=s_status.c_str();
        pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(C_Status);

        cout<<"Frame #"<<i+1<<"..."<<endl;
        string imageFileName;
        std::stringstream StrStm;
        StrStm<<i+1;
        StrStm>>imageFileName;
        imageFileName += ".bmp";
        //cv::Mat image = imread("F:\\采集小靶标\\1.bmp"); 
        cv::Mat image = imread(imageFileName); 
        /* 提取角点 */   
        Mat imageGray;
        cvtColor(image, imageGray , CV_RGB2GRAY);//转换成灰度图
        //imwrite("D:\\666.bmp", imageGray);

        //查找角点
        //bool patternfound = findChessboardCorners(imageGray, board_size, corners,+ CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE + CALIB_CB_FAST_CHECK);
        bool patternfound = findChessboardCorners(imageGray, board_size, corners,CALIB_CB_FAST_CHECK);
        if (!patternfound)   
        {   
            //AfxMessageBox(_T("没有发现角点坐标！")); 
            //continue;
            //exit(1);  
            char ch_sf[20];
            itoa(i+1,ch_sf,10);
            string s_status;
            s_status=s_status+"第"+ch_sf+"张图,没有发现角点坐标！";
            CString C_Status;
            C_Status=s_status.c_str();
            pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(C_Status);
            AfxMessageBox(C_Status);
            bImageFindCorner[i]=false;   //没有找到角点
        } 
        else
        {   
            bImageFindCorner[i]=true;   //找到角点
            /* 亚像素精确化 */
            cornerSubPix(imageGray, corners, Size(11, 11), Size(-1, -1), TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));

            /* 绘制检测到的角点并保存 */
            Mat imageTemp = image.clone();
            for (int j = 0; j < corners.size(); j++)
            {
            circle( imageTemp, corners[j], 10, Scalar(0,0,255), 2, 8, 0);
            }
            string imageFileName;
            std::stringstream StrStm;
            StrStm<<i+1;
            StrStm>>imageFileName;
            imageFileName += "_corner.jpg";
            imwrite(imageFileName,imageTemp);
            cout<<"Frame corner#"<<i+1<<"...end"<<endl;

            count = count + corners.size();
            successImageNum = successImageNum + 1;
            corners_Seq.push_back(corners);
            //#########################################
            char ch_sf[20];
            itoa(i+1,ch_sf,10);
            string s_status;
            s_status=s_status+"第"+ch_sf+"张图,角点提取完成!";
            CString C_Status;
            C_Status=s_status.c_str();
            pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(C_Status);
        }   
        image_Seq.push_back(image);
    }   
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("角点提取完成!"));
    //AfxMessageBox(_T("角点提取完成！")); 
    /************************************************************************  
    摄像机定标  
    *************************************************************************/
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("开始定标…"));
    //AfxMessageBox(_T("开始定标………………")); 
    Size square_size = Size(150,150);     //标定板尺寸？？ 
    vector<vector<Point3f>>  object_Points;        /****  保存定标板上角点的三维坐标   ****/

    Mat image_points = Mat(1, count, CV_32FC2, Scalar::all(0));  /*****   保存提取的所有角点   *****/
    vector<int>  point_counts;                                                         
    /* 初始化定标板上角点的三维坐标 */
    for (int t = 0; t<successImageNum; t++)
    {
        vector<Point3f> tempPointSet;
        for (int i = 0; i<board_size.height; i++)
        {
            for (int j = 0; j<board_size.width; j++)
            {
                /* 假设定标板放在世界坐标系中z=0的平面上 */
                Point3f tempPoint;
                tempPoint.x = i*square_size.width;
                tempPoint.y = j*square_size.height;
                tempPoint.z = 0;
                tempPointSet.push_back(tempPoint);
            }
        }
        object_Points.push_back(tempPointSet);
    }
    for (int i = 0; i< successImageNum; i++)
    {
        point_counts.push_back(board_size.width*board_size.height);
    }
    /* 开始定标 */
    Size image_size = image_Seq[0].size();
    //cv::Matx33d intrinsic_matrix;    /*****    摄像机内参数矩阵    ****/
    //cv::Vec4d distortion_coeffs;     /* 摄像机的4个畸变系数：k1,k2,k3,k4*/
    //std::vector<cv::Vec3d> rotation_vectors;                           /* 每幅图像的旋转向量 */
    //std::vector<cv::Vec3d> translation_vectors;                        /* 每幅图像的平移向量 */
    int flags = 0;
    flags |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
    flags |= cv::fisheye::CALIB_CHECK_COND;
    flags |= cv::fisheye::CALIB_FIX_SKEW;
    //cv::TermCriteria(3, 20, 1e-6)
    //cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 100, DBL_EPSILON)
    double rms =fisheye::calibrate(object_Points, corners_Seq, image_size, intrinsic_matrix, distortion_coeffs, rotation_vectors, translation_vectors, flags,cv::TermCriteria(3, 20, 1e-6));
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("标定完成！"));
    //AfxMessageBox(_T("标定完成！"));
    /**********************************************************************  
    对定标结果进行评价  
    **********************************************************************/   

    //cout<<"开始评价定标结果………………"<<endl;   
    double total_err = 0.0;                   /* 所有图像的平均误差的总和 */   
    double err = 0.0;                        /* 每幅图像的平均误差 */   
    vector<Point2f>  image_points2;             /****   保存重新计算得到的投影点    ****/   

    //cout<<"每幅图像的定标误差："<<endl;   
    //cout<<"每幅图像的定标误差："<<endl<<endl;

    float f_total_err=0;  //总体误差
    for (int i=0;  i<image_count;  i++) 
    {
        if (bImageFindCorner[i])//找到角点再执行相关计算
        {
            vector<Point3f> tempPointSet = object_Points[i];
            /****  通过得到的摄像机内外参数，对空间的三维点进行重新投影计算，得到新的投影点     ****/
            fisheye::projectPoints(tempPointSet, image_points2, rotation_vectors[i], translation_vectors[i], intrinsic_matrix, distortion_coeffs);
            /* 计算新的投影点和旧的投影点之间的误差*/  
            vector<Point2f> tempImagePoint = corners_Seq[i];
            Mat tempImagePointMat = Mat(1,tempImagePoint.size(),CV_32FC2);
            Mat image_points2Mat = Mat(1,image_points2.size(), CV_32FC2);
            for (size_t i = 0 ; i != tempImagePoint.size(); i++)
            {
                image_points2Mat.at<Vec2f>(0,i) = Vec2f(image_points2[i].x, image_points2[i].y);
                tempImagePointMat.at<Vec2f>(0,i) = Vec2f(tempImagePoint[i].x, tempImagePoint[i].y);
            }
            err = norm(image_points2Mat, tempImagePointMat, NORM_INF);//求取最大值
            float f_err=0;

            f_err=err;
            total_err += err/=  point_counts[i];   
            f_total_err+=f_err;
            //cout<<"第"<<i+1<<"幅图像的平均误差："<<err<<"像素"<<endl;   
            fout<<"第"<<i+1<<"幅图像的最大误差："<<f_err<<"像素"<<endl; 
        }
    }   
    //cout<<"总体平均误差："<<total_err/successImageNum<<"像素"<<endl;   
    //fout<<"总体平均误差："<<total_err/successImageNum<<"像素"<<endl<<endl;
    fout<<"总体最大误差均值："<<f_total_err/successImageNum<<"像素"<<endl<<endl;
    //cout<<"评价完成！"<<endl;   

    /*********************************************************************  
    保存定标结果  
    **********************************************************************/   
    //cout<<"开始保存定标结果………………"<<endl;     
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("开始保存标定结果…"));
    Mat rotation_matrix = Mat(3,3,CV_32FC1, Scalar::all(0)); /* 保存每幅图像的旋转矩阵 */   

    fout<<"相机内参数矩阵："<<endl;   
    fout<<intrinsic_matrix<<endl;   
    fout<<"畸变系数：\n";   
    fout<<distortion_coeffs<<endl;   
    for (int i=0; i<image_count; i++) 
    { 
        if (bImageFindCorner[i])//找到角点的图参与相关计算
        {
            fout<<"第"<<i+1<<"幅图像的旋转向量："<<endl;   
            fout<<rotation_vectors[i]<<endl;   

            /* 将旋转向量转换为相对应的旋转矩阵 */   
            Rodrigues(rotation_vectors[i],rotation_matrix);   
            fout<<"第"<<i+1<<"幅图像的旋转矩阵："<<endl;   
            fout<<rotation_matrix<<endl;   
            fout<<"第"<<i+1<<"幅图像的平移向量："<<endl;   
            fout<<translation_vectors[i]<<endl;   
        }
    }  
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("标定结果保存完成！"));
    //cout<<"完成保存"<<endl; 
    fout<<endl;
    /*********************************************************************  
    显示定标结果  
    ***********************************************************************/
    Mat mapx = Mat(image_size,CV_32FC1);
    Mat mapy = Mat(image_size,CV_32FC1);
    Mat R = Mat::eye(3,3,CV_32F);
    //cout<<"保存矫正图像"<<endl;
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("开始保存矫正图像..."));
    for (int i = 0 ; i != image_count ; i++)
    {
        if (bImageFindCorner[i])//找到角点的图参与相关计算
        {
            cout<<"Frame #"<<i+1<<"..."<<endl;
            Mat newCameraMatrix = Mat(3,3,CV_32FC1,Scalar::all(0));
            fisheye::initUndistortRectifyMap(intrinsic_matrix,distortion_coeffs,R,intrinsic_matrix,image_size,CV_32FC1,mapx,mapy);
            Mat t = image_Seq[i].clone();
            cv::remap(image_Seq[i],t,mapx, mapy, INTER_LINEAR);
            string imageFileName;
            std::stringstream StrStm;
            StrStm<<i+1;
            StrStm>>imageFileName;
            imageFileName += "_d.jpg";
            imwrite(imageFileName,t);
        }
    }
    pWnd->GetDlgItem(IDC_Status_EDIT)->SetWindowTextW(_T("矫正图像保存结束！"));
    //cout<<"保存结束"<<endl;
    /**********************************************************************  
    测试一张图片  
    *********************************************************************/
    //if (1)
    //{
    //  cout<<"TestImage ..."<<endl;
    //  Mat newCameraMatrix = Mat(3,3,CV_32FC1,Scalar::all(0));
    //  Mat testImage = imread("F:\\9-19新靶标26x24\\1.bmp",1);
    //  fisheye::initUndistortRectifyMap(intrinsic_matrix,distortion_coeffs,R,intrinsic_matrix,image_size,CV_32FC1,mapx,mapy);
    //  Mat t = testImage.clone();
    //  cv::remap(testImage,t,mapx, mapy, INTER_LINEAR);

    //  imwrite("TestOutput.jpg",t);
    //  cout<<"保存结束"<<endl;
    //}
    //AfxMessageBox(_T("校正完成！")); 

    return 0;
}

鱼眼镜头拍摄原图

校正效果图

在进行鱼眼镜头校正时，采集的校正图像一定要多角度拍摄，确保各个方向各个角度都有棋盘格靶标，而且棋盘格靶标占整个图片2/3左右比较合适。