OpenCV_Camera Calibration and Rectification under QT creator( 相机标定及矫正 | QT creator环境 )

小鱼儿 2022-10-01 04:44 234阅读 0赞

流程：

//1.找多副棋盘格图像角点,存入2D图像点及3D坐标点  
//2.进行相机标定 获取标定参数：相机矩阵 畸变矩阵 旋转向量和平移向量  
//3.映射相应矩阵 获取x y映射函数 (像高hi/物高h0=焦距f/物距d0)  
//4.应用映射函数，输出未畸变图像

main 函数：

#include <QCoreApplication>
    
    #include <opencv2/core/core.hpp>
    #include <opencv2/highgui/highgui.hpp>
    #include <opencv2/features2d/features2d.hpp> //引用cv::KeyPoint 特征检测器通用接口
    # include <opencv2/calib3d/calib3d.hpp>
    //#include <opencv2/legacy/legacy.hpp>   //引用cv::cornerSubPix()
    #include  "CameraCalibrator.h"
    #include  <iostream>
    #include <iomanip>
    int main(int argc, char *argv[])
    {
        QCoreApplication a(argc, argv);
        //2.使用CameraCalibritor类对图像进行矫正
           //cv::Mat image = cv::imread("../../aTestImage/chessboards/chessboard01.jpg", 0);
    
            //cv::namedWindow("Image");
    
           cv::Mat image;
            std::vector<std::string> filelist  ;  //????初始化
            for (int i = 1; i <= 20; i++)//将指定文件夹中20张图片添加到filelist中
            {
               std::stringstream str;
               str << "../TestPic/chessboards/chessboard" << std::setw(2) << std::setfill('0') << i << ".jpg";
               std::cout << str.str() << std::endl;
               filelist.push_back(str.str());
               image = cv::imread(str.str(), 0);
    
            //cv::imshow("Image", image);
            //cv::waitKey(100);
            }
    
            CameraCalibrator calibr;
            cv::Size boardSize(6, 4);
            calibr.addChessboardPoints(filelist, boardSize);:imread( filelist[0]);
            cv::Size cvsize =cv::Size(320,240);
             //指定标定文件夹  标定尺寸
            //image =cv: calibr.calibrate(cvsize);  //进行标定image.size()
    
            image =cv::imread( filelist[11]);
            cv::Mat result = calibr.remap(image);  //进行矫正
    
            cv::namedWindow("image");  //显示src
            cv::imshow("image", image);
            cv::namedWindow("result");  //显示结果
            cv::imshow("result", result);
    
            cv::waitKey(0);
    
        return a.exec();
    }

CameraCalibrator.h 头文件：

#pragma once
    #include <opencv2/core/core.hpp>
    #include <opencv2/highgui/highgui.hpp>
    #include <opencv2/features2d/features2d.hpp> //引用cv::KeyPoint 特征检测器通用接口
    #include <opencv2/imgproc/imgproc.hpp>
    # include <opencv2/calib3d/calib3d.hpp>
    //#include <opencv2/legacy/legacy.hpp>   //引用cv::cornerSubPix()
    class CameraCalibrator
    {
    public:
        CameraCalibrator() ;
    
    	 ~CameraCalibrator();
    	//提取 文件中各个图像 指定数目 棋盘格角点
    	int addChessboardPoints(const std::vector<std::string>&filelist, cv::Size &boardSize);
    	//添加角点到2D图像点和3D场景点坐标系中
    	void addPoints(const std::vector<cv::Point2f> &imageCorners, const std::vector<cv::Point3f> &objectCorners);
    	//进行标定，并返回投影误差(相机矩阵，畸变矩阵，旋转向量，平移向量)
        double  calibrate(cv::Size &imageSize);
    	//标定后去除图像中的畸变
    	cv::Mat remap(const cv::Mat &image);
    private:
        std::vector< std::vector<cv::Point3f> >objectPoints;  //存储世界坐标点
        std::vector< std::vector<cv::Point2f> >imagePoints;  //存储像素坐标点
    	cv::Mat  cameraMatrix;  //输出相机矩阵
    	cv::Mat  distCoeffs;    //输出畸变矩阵
    	int flag;  //标定方式
    	cv::Mat map1, map2;  //去图像畸变的x y 映射函数
    	bool mustInitUndistort;  //是否初始化失真
    	
    };

CameraCalibrator.cpp:

#include "CameraCalibrator.h"
    //#include <opencv2/core/core.hpp>
    //#include <opencv2/highgui/highgui.hpp>
    //#include <opencv2/features2d/features2d.hpp> //引用cv::KeyPoint 特征检测器通用接口
    //# include <opencv2/calib3d/calib3d.hpp>
    //#include <opencv2/legacy/legacy.hpp>   //引用cv::cornerSubPix()
    
    CameraCalibrator::CameraCalibrator()
    {
        flag=0;
        mustInitUndistort=true;
    }
    
    
    CameraCalibrator::~CameraCalibrator()
    {
    }
    
    int CameraCalibrator::addChessboardPoints(const std::vector<std::string>& filelist, cv::Size & boardSize)
    {
    	std::vector< cv::Point2f> imageCorners;  //对应图像上(i, j)棋盘格角点
    	std::vector< cv::Point3f> objectCorners;  //对应世界坐标系(X,Y,Z)棋盘格角点
    	//获取3D场景中的点
    	for (int i = 0; i < boardSize.height; i++)
    	{
    		for (int j = 0; j < boardSize.width; j++)
    		{
    			objectCorners.push_back(cv::Point3f(i, j, 0.0f));
    		}
    	}
    
    	//获取2D图像中的点
    	cv::Mat  image;
    	int successes = 0;
    	for (int i = 0; i < filelist.size(); i++)
    	{
    	      image = cv::imread(filelist[i], 0);
            bool found = cv::findChessboardCorners(image, boardSize, imageCorners); //获取棋盘格角点  ?? under VS "block type is valid"
           // cv::cornerSubPix(image, imageCorners, cv::Size(5, 5), cv::Size(-1, -1),  //获取亚像素精度
             //    cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 30, 0.1)); //终止条件为迭代30次或达到精度0.1
    		
            if (imageCorners.size() == boardSize.area())
            {
                addPoints(imageCorners, objectCorners);
                successes++;
            }
    	}  
    	return successes;  //block type is valid
    }
    
    void CameraCalibrator::addPoints(const std::vector<cv::Point2f>& imageCorners, const std::vector<cv::Point3f>& objectCorners)
    {
    	imagePoints.push_back(imageCorners);
    	objectPoints.push_back(objectCorners);
    }
    
    double CameraCalibrator::calibrate(cv::Size &imageSize)
    {
    	mustInitUndistort = true;  //必须重新去畸变
    	std::vector<cv::Mat> rvecs, tvecs;  //输出旋转向量和平移向量
    	return  calibrateCamera(objectPoints,imagePoints,imageSize,cameraMatrix,distCoeffs,rvecs,tvecs,flag);
    }
    
    cv::Mat CameraCalibrator::remap(const cv::Mat & image)
    {
    	cv::Mat undistorted; //未畸变图像
        if (mustInitUndistort)
        {
            //初始化未畸变矫正映射图像(相机矩阵，畸变矩阵，可选矫正矩阵，生成的未畸变相机矩阵，生成的未畸变相机矩阵的尺寸，输出的映射图像类型，X坐标映射函数，Y坐标映射函数)
            cv::initUndistortRectifyMap(cameraMatrix, distCoeffs, cv::Mat(), cv::Mat(),cv::Size(320,240), CV_32FC1, map1, map2);
            mustInitUndistort = false;
        }
        cv::remap(image, undistorted, map1, map2,cv::INTER_LINEAR);  //应用映射函数，输出未畸变图像  | 差值类型
    	return undistorted;
    }

![20170326105147940][]![20170326105158894][]

[20170326105147940]: https://img-blog.csdn.net/20170326105147940
[20170326105158894]: /images/20220705/58dc6b15c2cf47818c7bb9045274b683.png