利用相机内外参读取矫正后的视频流

主要目的

---

• 利用所得到的内外参矩阵读取矫正后的相机的视频流
  （因为用到的摄像头是红外线摄像头（监控摄像头），有必要了解其原理）从光谱来讲，和普通摄像头感可见光原理类似。红外摄像头工作原理是红外灯发出红外线照射物体，红外线漫反射，被监控摄像头接收，形成视频图像。

  程序源码

  整个项目主要包括以下程序

  
  

  main.cpp

  
  

  
  include 
        
        
  include <opencv2/opencv.hpp>
  include 
        
        
  include"CameraCalibrator.h"
  using namespace cv;
  
  using namespace std;

int main()
{
VideoCapture capture(1);
CameraCalibrator cameraCalibrator;
if (capture.isOpened())
{
cout << "success" << endl;
}
Mat frame;
Mat ROI;
while (capture.isOpened())
{
capture >> frame;
Mat uImage = cameraCalibrator.remap(frame);
ROI = uImage(Rect(60, 0, 560, 410));
imshow("video1", ROI);
cout << uImage.size() << endl;
char key = static_cast (waitKey(50));//控制视频流的帧率，50ms一帧
if (key == 27) //按esc退出
break;
}
return 0;
}


calibrate.h()

  
class CameraCalibrator {
        vector
   
   
    
    > objectPoints;
        vector
    
    
     
     > imagePoints;
        
        Mat cameraMatrix;
        Mat distCoeffs;
        
        int flag;
        
        Mat map1, map2;
        bool mustInitUndistort;
    
        public:
            CameraCalibrator() : flag(0), mustInitUndistort(true) {};
        
            int addChessboardPoints(const std::vector
     
     
      
      & filelist, cv::Size & boardSize);
                // Add scene points and corresponding image points
            void addPoints(const std::vector
      
      
       
       & imageCorners, const std::vector
       
       
         & objectCorners); // Calibrate the camera double calibrate(cv::Size &imageSize); // Set the calibration flag void setCalibrationFlag(bool radial8CoeffEnabled = false, bool tangentialParamEnabled = false); // Remove distortion in an image (after calibration) cv::Mat CameraCalibrator::remap(const cv::Mat &image); // Getters cv::Mat getCameraMatrix() { return cameraMatrix; } cv::Mat getDistCoeffs() { return distCoeffs; } }; 
       
      
      
     
     
    
    
   
   

CameraCalibrator.cpp

  
        #include "CameraCalibrator.h"
    using namespace cv;
    cv::Mat CameraCalibrator::remap(const cv::Mat &image) {
        
                cv::Mat undistorted;
                    cv::Mat cameraMatrix = cv::Mat::eye(3, 3, CV_64F);

    //内参矩阵
    cameraMatrix.at
   
   
    
    (0, 0) = 304.5343301172393;
    cameraMatrix.at
    
    
     
     (0, 1) = 0;
    cameraMatrix.at
     
     
      
      (0, 2) = 355.6868747437238;
    cameraMatrix.at
      
      
       
       (1, 0) = 0;
    cameraMatrix.at
       
       
         (1, 1) = 304.4062190996952; cameraMatrix.at 
        
          (1, 2) = 275.6767450385067; cameraMatrix.at 
         
           (2, 0) = 0; cameraMatrix.at 
          
            (2, 1) = 0; cameraMatrix.at 
           
             (2, 2) = 1; //畸变参数 cv::Mat distCoeffs = cv::Mat::zeros(5, 1, CV_64F); distCoeffs.at 
            
              (0, 0) = -0.3559459318901729; distCoeffs.at 
             
               (1, 0) = 0.1634235977115495; distCoeffs.at 
              
                (2, 0) = 0.000291221640019827; distCoeffs.at 
               
                 (3, 0) = 0.002862694736722168; distCoeffs.at 
                
                  (4, 0) = -0.04160147169190362; if (mustInitUndistort) { // called once per calibration cv::initUndistortRectifyMap( cameraMatrix, // computed camera matrix distCoeffs, // computed distortion matrix cv::Mat(), // optional rectification (none) cv::Mat(), // camera matrix to generate undistorted cv::Size(720, 540), // image.size(), // size of undistorted CV_32FC1, // type of output map map1, map2); // the x and y mapping functions mustInitUndistort = false; } // Apply mapping functions cv::remap(image, undistorted, map1, map2, cv::INTER_LINEAR); // interpolation type return undistorted; }