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 
#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::vectorstd::string& filelist, cv::Size & boardSize);

// Add scene points and corresponding image points

void addPoints(const std::vectorcv::Point2f& imageCorners, const std::vectorcv::Point3f& 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;

}