OPENCV3.0 单目摄像头标定(使用官方自带的标定图片)

  
  
// opencv_test.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"
#include <opencv2/opencv.hpp>
#include <highgui.hpp>
#include "cv.h"
#include <cv.hpp>
#include <iostream>

using namespace std;
using namespace cv;

const int imageWidth = 640; //摄像头的分辨率
const int imageHeight = 480;
const int boardWidth = 9; //横向的角点数目
const int boardHeight = 6; //纵向的角点数据
const int boardCorner = boardWidth * boardHeight; //总的角点数据
const int frameNumber = 13; //相机标定时需要采用的图像帧数
const int squareSize = 20; //标定板黑白格子的大小 单位mm
const Size boardSize = Size(boardWidth, boardHeight); //

Mat intrinsic; //相机内参数
Mat distortion_coeff; //相机畸变参数
vector<Mat> rvecs; //旋转向量
vector<Mat> tvecs; //平移向量
vector< vector<Point2f>> corners; //各个图像找到的角点的集合 和objRealPoint 一一对应
vector< vector<Point3f>> objRealPoint; //各副图像的角点的实际物理坐标集合


vector<Point2f> corner; //某一副图像找到的角点

Mat rgbImage, grayImage;

/*计算标定板上模块的实际物理坐标*/
void calRealPoint(vector<vector<Point3f>>& obj, int boardwidth,int boardheight, int imgNumber, int squaresize)
{
// Mat imgpoint(boardheight, boardwidth, CV_32FC3,Scalar(0,0,0));
vector<Point3f> imgpoint;
for ( int rowIndex = 0; rowIndex < boardheight; rowIndex++)
{
for ( int colIndex = 0; colIndex < boardwidth; colIndex++)
{
// imgpoint.at<Vec3f>(rowIndex, colIndex) = Vec3f(rowIndex * squaresize, colIndex*squaresize, 0);
imgpoint.push_back(Point3f(rowIndex * squaresize, colIndex * squaresize, 0));
}
}
for ( int imgIndex = 0; imgIndex < imgNumber; imgIndex++)
{
obj.push_back(imgpoint);
}
}

/*设置相机的初始参数 也可以不估计*/
void guessCameraParam(void )
{
/*分配内存*/
intrinsic.create( 3, 3, CV_64FC1);
distortion_coeff.create( 5, 1, CV_64FC1);

/*
fx 0 cx
0 fy cy
0 0 1
*/
intrinsic.at< double>( 0, 0) = 256.8093262; //fx
intrinsic.at< double>( 0, 2) = 160.2826538; //cx
intrinsic.at< double>( 1, 1) = 254.7511139; //fy
intrinsic.at< double>( 1, 2) = 127.6264572; //cy

intrinsic.at< double>( 0, 1) = 0;
intrinsic.at< double>( 1, 0) = 0;
intrinsic.at< double>( 2, 0) = 0;
intrinsic.at< double>( 2, 1) = 0;
intrinsic.at< double>( 2, 2) = 1;

/*
k1 k2 p1 p2 p3
*/
distortion_coeff.at< double>( 0, 0) = -0.193740; //k1
distortion_coeff.at< double>( 1, 0) = -0.378588; //k2
distortion_coeff.at< double>( 2, 0) = 0.028980; //p1
distortion_coeff.at< double>( 3, 0) = 0.008136; //p2
distortion_coeff.at< double>( 4, 0) = 0; //p3
}

void outputCameraParam(void )
{
/*保存数据*/
//cvSave("cameraMatrix.xml", &intrinsic);
//cvSave("cameraDistoration.xml", &distortion_coeff);
//cvSave("rotatoVector.xml", &rvecs);
//cvSave("translationVector.xml", &tvecs);
/*输出数据*/
cout << "fx :" << intrinsic.at< double>( 0, 0) << endl << "fy :" << intrinsic.at< double>( 1, 1) << endl;
cout << "cx :" << intrinsic.at< double>( 0, 2) << endl << "cy :" << intrinsic.at< double>( 1, 2) << endl;

cout << "k1 :" << distortion_coeff.at< double>( 0, 0) << endl;
cout << "k2 :" << distortion_coeff.at< double>( 1, 0) << endl;
cout << "p1 :" << distortion_coeff.at< double>( 2, 0) << endl;
cout << "p2 :" << distortion_coeff.at< double>( 3, 0) << endl;
cout << "p3 :" << distortion_coeff.at< double>( 4, 0) << endl;
}


int _tmain( int argc, _TCHAR* argv[])
{
Mat img;
int goodFrameCount = 0;
namedWindow( "chessboard");
cout << "按Q退出 ..." << endl;
while (goodFrameCount < frameNumber)
{
char filename[ 100];
sprintf_s(filename, "image\\left%02d.jpg", goodFrameCount + 1);
// cout << filename << endl;
rgbImage = imread(filename, CV_LOAD_IMAGE_COLOR);
cvtColor(rgbImage, grayImage, CV_BGR2GRAY);
imshow( "Camera", grayImage);

bool isFind = findChessboardCorners(rgbImage, boardSize, corner, 0);
if (isFind == true) //所有角点都被找到 说明这幅图像是可行的
{
/*
Size(5,5) 搜索窗口的一半大小
Size(-1,-1) 死区的一半尺寸
TermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 20, 0.1)迭代终止条件
*/
cornerSubPix(grayImage, corner, Size( 5, 5), Size( -1, -1), TermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 20, 0.1));
drawChessboardCorners(rgbImage, boardSize, corner, isFind);
imshow( "chessboard", rgbImage);
corners.push_back(corner);
//string filename = "res\\image\\calibration";
//filename += goodFrameCount + ".jpg";
//cvSaveImage(filename.c_str(), &IplImage(rgbImage)); //把合格的图片保存起来
goodFrameCount++;
cout << "The image is good" << endl;
}
else
{
cout << "The image is bad please try again" << endl;
}
// cout << "Press any key to continue..." << endl;
// waitKey(0);

if (waitKey( 10) == 'q')
{
break;
}
// imshow("chessboard", rgbImage);
}

/*
图像采集完毕 接下来开始摄像头的校正
calibrateCamera()
输入参数 objectPoints 角点的实际物理坐标
imagePoints 角点的图像坐标
imageSize 图像的大小
输出参数
cameraMatrix 相机的内参矩阵
distCoeffs 相机的畸变参数
rvecs 旋转矢量(外参数)
tvecs 平移矢量(外参数）
*/

/*设置实际初始参数 根据calibrateCamera来 如果flag = 0 也可以不进行设置*/
guessCameraParam();
cout << "guess successful" << endl;
/*计算实际的校正点的三维坐标*/
calRealPoint(objRealPoint, boardWidth, boardHeight,frameNumber, squareSize);
cout << "cal real successful" << endl;
/*标定摄像头*/
calibrateCamera(objRealPoint, corners, Size(imageWidth, imageHeight), intrinsic, distortion_coeff, rvecs, tvecs, 0);
cout << "calibration successful" << endl;
/*保存并输出参数*/
outputCameraParam();
cout << "out successful" << endl;

/*显示畸变校正效果*/
Mat cImage;
undistort(rgbImage, cImage, intrinsic, distortion_coeff);
imshow( "Corret Image", cImage);
cout << "Correct Image" << endl;
cout << "Wait for Key" << endl;
waitKey( 0);
system( "pause");
return 0;
}
  
  

OPENCV3.0版本跟2.x版本是有一点差距的，这个程序在2.4.11版本里面跑不起来。

找了很久都没有找到错误，主要是在calibrateCamera()函数的时候出错。

也参考了官方的calibration例程，但还是找不到错误在什么地方。

下面是3.0版本的代码 注释都在代码里面

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