使用OpenCV标定鱼眼镜头（C++）

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使用OpenCV标定鱼眼镜头（C++）

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一、使用的函数

  由于鱼眼镜头和针孔镜头的模型不一样，对于鱼眼镜头的模型在之前的博客中已经做了详细介绍，这里直接使用OpenCV中的cv::fisheye::calibrate()函数进行标定。函数原型如下，需要输入目标点集，图像点集、图像尺寸。函数输出相机内参，畸变系数，旋转矩阵和平移向量，以及反投影误差。

 CV_EXPORTS double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size,
        InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
            TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));

二、采集标定图像

  采集若干拍摄有标定棋盘格的图像，并使棋盘格出现在画面的各个位置，特别是边缘位置。如下图所示：

三、标定代码

#include "stdio.h"
#include <iostream>
#include <fstream>
#include <io.h>

#include "opencv2/opencv.hpp"
#include <opencv2/core/core.hpp>
#include "opencv2/calib3d/calib3d.hpp"
#include <opencv2/highgui/highgui.hpp>

using namespace std;
using namespace cv;

void getFiles(string path, vector<string>& files)
{
    //文件句柄
    intptr_t hFile = 0;
    //文件信息
    struct _finddata_t fileinfo;
    string p;
    if ((hFile = _findfirst(p.assign(path).append("\\*").c_str(), &fileinfo)) != -1)
    {
        do
        {
            //如果是目录,迭代之
            //如果不是,加入列表
            if ((fileinfo.attrib &  _A_SUBDIR))
            {
                if (strcmp(fileinfo.name, ".") != 0 && strcmp(fileinfo.name, "..") != 0)
                    getFiles(p.assign(path).append("\\").append(fileinfo.name), files);
            }
            else
            {
                files.push_back(p.assign(path).append("\\").append(fileinfo.name));
            }
        } while (_findnext(hFile, &fileinfo) == 0);
        _findclose(hFile);
    }
}

int main(int argc, char** argv)
{   
    string filePath = ".\\720PPcalib\\front";
    vector<string> files;

    ////获取该路径下的所有文件
    getFiles(filePath, files);

    const int board_w = 6;
    const int board_h = 4;
    const int NPoints = board_w * board_h;//棋盘格内角点总数
    const int boardSize = 30; //mm
    Mat image,grayimage;
    Size ChessBoardSize = cv::Size(board_w, board_h);
    vector<Point2f> tempcorners;

    int flag = 0;
    flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
    //flag |= cv::fisheye::CALIB_CHECK_COND;
    flag |= cv::fisheye::CALIB_FIX_SKEW;
    //flag |= cv::fisheye::CALIB_USE_INTRINSIC_GUESS;

    vector<Point3f> object;
    for (int j = 0; j < NPoints; j++)
    {
        object.push_back(Point3f((j % board_w) * boardSize, (j / board_w) * boardSize, 0)); 
    }

    cv::Matx33d intrinsics;//z:相机内参
    cv::Vec4d distortion_coeff;//z:相机畸变系数

    vector<vector<Point3f> > objectv;
    vector<vector<Point2f> > imagev;

    Size corrected_size(1280, 720);
    Mat mapx, mapy;
    Mat corrected;

    ofstream intrinsicfile("intrinsics_front1103.txt");
    ofstream disfile("dis_coeff_front1103.txt");
    int num = 0;
    bool bCalib = false;
    while (num < files.size())
    {
        image = imread(files[num]);

        if (image.empty())
            break;
        imshow("corner_image", image);
        waitKey(10);
        cvtColor(image, grayimage, CV_BGR2GRAY);
        IplImage tempgray = grayimage;
        bool findchessboard = cvCheckChessboard(&tempgray, ChessBoardSize);

        if (findchessboard)
        {
            bool find_corners_result = findChessboardCorners(grayimage, ChessBoardSize, tempcorners, 3);
            if (find_corners_result)
            {
                cornerSubPix(grayimage, tempcorners, cvSize(5, 5), cvSize(-1, -1), cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
                drawChessboardCorners(image, ChessBoardSize, tempcorners, find_corners_result);
                imshow("corner_image", image);
                cvWaitKey(100);

                objectv.push_back(object);
                imagev.push_back(tempcorners);
                cout << "capture " << num << " pictures" << endl;
            }
        }
        tempcorners.clear();
        num++;
    }

    cv::fisheye::calibrate(objectv, imagev, cv::Size(image.cols,image.rows), intrinsics, distortion_coeff, cv::noArray(), cv::noArray(), flag, cv::TermCriteria(3, 20, 1e-6));  
    fisheye::initUndistortRectifyMap(intrinsics, distortion_coeff, cv::Matx33d::eye(), intrinsics, corrected_size, CV_16SC2, mapx, mapy);

    for(int i=0; i<3; ++i)
    {
        for(int j=0; j<3; ++j)
        {
            intrinsicfile<<intrinsics(i,j)<<"\t";
        }
        intrinsicfile<<endl;
    }
    for(int i=0; i<4; ++i)
    {
        disfile<<distortion_coeff(i)<<"\t";
    }
    intrinsicfile.close();
    disfile.close();

    num = 0;
    while (num < files.size())
    {
        image = imread(files[num++]);

        if (image.empty())
            break;
        remap(image, corrected, mapx, mapy, INTER_LINEAR, BORDER_TRANSPARENT);

        imshow("corner_image", image);
        imshow("corrected", corrected);
        cvWaitKey(200); 
    }

    cv::destroyWindow("corner_image");
    cv::destroyWindow("corrected");

    image.release();
    grayimage.release();
    corrected.release();
    mapx.release();
    mapy.release();

    return 0;
}

四、标定结果

  使用标定的结果进行畸变校正后的结果如下所示，可以看到，原本弯曲的曲线已经变直。