使用opencv进行双目相机标定
一、利用相机拍摄保存相片
拍摄保存想拍摄棋盘局相片，用来做相机标定。
#include
#include
using namespace cv;
using namespace std;
void main()
{
VideoCapture cap;
cap.open(0); //打开摄像头
if (!cap.isOpened())//如果视频不能正常打开则返回
return;
cvWaitKey(30);
Mat frame;//用于保存每一帧图像
cap >> frame;
imshow("【双目原始视图】", frame);
cvWaitKey(300);
char buf[30] = { 0 }; //保存路径变量
while (1)
{
cap >> frame; //等价于cap.read(frame);
if (frame.empty()) //如果某帧为空则退出循环
break;
imshow("【双目原始视图】", frame); //显示双目原始图像 原始分辨率为 640*480
Mat DoubleImage;
resize(frame, DoubleImage, Size(640, 240), (0, 0), (0, 0), INTER_AREA); // 纵向分辨率缩小一半
imshow("【双目缩小视图】", DoubleImage); //显示图像
Mat LeftImage = DoubleImage(Rect(0, 0, 320, 240)); //分割得到左视图
Mat RightImage = DoubleImage(Rect(320, 0, 320, 240)); //分割得到右视图
imshow("【左视图】", LeftImage); //显示左视图
imshow("【右视图】", RightImage); //显示右视图
char c = cvWaitKey(30);
if (c == 27)//Esc键退出
{
break;
}
static int i = 9;
if (13 == char(c))
{
sprintf(buf, ".\\picture\\left_%d.png", i); //保存左视图
cout << buf;
imwrite(buf, LeftImage);
sprintf(buf, ".\\picture\\right_%d.png", i); //保存右视图
imwrite(buf, RightImage);
sprintf(buf, ".\\picture\\total_%d.png", i); //保存整体图像
imwrite(buf, DoubleImage);
i++;
}
}
cap.release();//释放资源
} 二、相机标定
注意stereo_calibration.xml放置目录要准确，保证上一步骤拍摄的相片能够读到。
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
//此处参数需要根据棋盘格个数修改
//例如 黑白棋盘格 宽（w）为10个棋盘格 那么 w 为 10 -1 = 9
#define w 9 //棋盘格宽的黑白交叉点个数
#define h 6 //棋盘格高的黑白交叉点个数
const float chessboardSquareSize = 12.5f; //每个棋盘格方块的边长 单位 为 mm
using namespace std;
using namespace cv;
//从 xml 文件中读取图片存储路径
static bool readStringList(const string& filename, vector& list)
{
list.resize(0);
FileStorage fs(filename, FileStorage::READ);
if (!fs.isOpened())
return false;
FileNode n = fs.getFirstTopLevelNode();
if (n.type() != FileNode::SEQ)
return false;
FileNodeIterator it = n.begin(), it_end = n.end();
for (; it != it_end; ++it)
list.push_back((string)*it);
return true;
}
//记录棋盘格角点个数
static void calcChessboardCorners(Size boardSize, float squareSize, vector& corners)
{
corners.resize(0);
for (int i = 0; i < boardSize.height; i++) //height和width位置不能颠倒
for (int j = 0; j < boardSize.width; j++)
{
corners.push_back(Point3f(j * squareSize, i * squareSize, 0));
}
}
bool calibrate(Mat& intrMat, Mat& distCoeffs, vector>& imagePoints,
vector>& ObjectPoints, Size& imageSize, const int cameraId,
vector imageList)
{
double rms = 0; //重投影误差
Size boardSize;
boardSize.width = w;
boardSize.height = h;
vector pointBuf;
float squareSize = chessboardSquareSize;
vector rvecs, tvecs; //定义两个摄像头的旋转矩阵 和平移向量
bool ok = false;
int nImages = (int)imageList.size() / 2;
cout << "图片张数" << nImages;
namedWindow("View", 1);
int nums = 0; //有效棋盘格图片张数
for (int i = 0; i < nImages; i++)
{
Mat view, viewGray;
view = imread(imageList[i * 2 + cameraId], 1); //读取图片
imageSize = view.size();
cvtColor(view, viewGray, COLOR_BGR2GRAY); //转化成灰度图
bool found = findChessboardCorners(view, boardSize, pointBuf,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FAST_CHECK | CV_CALIB_CB_NORMALIZE_IMAGE); //寻找棋盘格角点
if (found)
{
nums++;
cornerSubPix(viewGray, pointBuf, Size(11, 11),
Size(-1, -1), TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
drawChessboardCorners(view, boardSize, Mat(pointBuf), found);
bitwise_not(view, view);
imagePoints.push_back(pointBuf);
cout << '.';
}
imshow("View", view);
waitKey(50);
}
cout << "有效棋盘格张数" << nums << endl;
//calculate chessboardCorners
calcChessboardCorners(boardSize, squareSize, ObjectPoints[0]);
ObjectPoints.resize(imagePoints.size(), ObjectPoints[0]);
rms = calibrateCamera(ObjectPoints, imagePoints, imageSize, intrMat, distCoeffs,
rvecs, tvecs);
ok = checkRange(intrMat) && checkRange(distCoeffs);
if (ok)
{
cout << "done with RMS error=" << rms << endl;
return true;
}
else
return false;
}
int main()
{
//initialize some parameters
bool okcalib = false;
Mat intrMatFirst, intrMatSec, distCoeffsFirst, distCoffesSec;
Mat R, T, E, F, RFirst, RSec, PFirst, PSec, Q;
vector> imagePointsFirst, imagePointsSec;
vector> ObjectPoints(1);
Rect validRoi[2];
Size imageSize;
int cameraIdFirst = 0, cameraIdSec = 1;
double rms = 0;
//get pictures and calibrate
vector imageList;
string filename = "D:\\desktop\\双目\\学习例程\\TestOpencv\\x64\\Debug\\stereo_calibration.xml";
bool okread = readStringList(filename, imageList);
if (!okread || imageList.empty())
{
cout << "can not open " << filename << " or the string list is empty" << endl;
return false;
}
if (imageList.size() % 2 != 0)
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return false;
}
FileStorage fs("intrinsics.yml", FileStorage::WRITE);
//calibrate
cout << "calibrate left camera..." << endl;
okcalib = calibrate(intrMatFirst, distCoeffsFirst, imagePointsFirst, ObjectPoints,
imageSize, cameraIdFirst, imageList);
if (!okcalib)
{
cout << "fail to calibrate left camera" << endl;
return -1;
}
else
{
cout << "calibrate the right camera..." << endl;
}
okcalib = calibrate(intrMatSec, distCoffesSec, imagePointsSec, ObjectPoints,
imageSize, cameraIdSec, imageList);
fs << "M1" << intrMatFirst << "D1" << distCoeffsFirst <<
"M2" << intrMatSec << "D2" << distCoffesSec;
if (!okcalib)
{
cout << "fail to calibrate the right camera" << endl;
return -1;
}
destroyAllWindows();
//estimate position and orientation
cout << "estimate position and orientation of the second camera" << endl
<< "relative to the first camera..." << endl;
cout << intrMatFirst;
cout << distCoeffsFirst;
cout << intrMatSec;
cout << distCoffesSec;
rms = stereoCalibrate(ObjectPoints, imagePointsFirst, imagePointsSec,
intrMatFirst, distCoeffsFirst, intrMatSec, distCoffesSec,
imageSize, R, T, E, F, CALIB_USE_INTRINSIC_GUESS,//CV_CALIB_FIX_INTRINSIC,
TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, 1e-6)); //计算重投影误差
cout << "done with RMS error=" << rms << endl;
//stereo rectify
cout << "stereo rectify..." << endl;
stereoRectify(intrMatFirst, distCoeffsFirst, intrMatSec, distCoffesSec, imageSize, R, T, RFirst,
RSec, PFirst, PSec, Q, CALIB_ZERO_DISPARITY, -1, imageSize, &validRoi[0], &validRoi[1]);
cout << "Q" << Q << endl;
cout << "P1" << PFirst << endl;
cout << "P2" << PSec << endl;
//read pictures for 3d-reconstruction
if (fs.isOpened())
{
cout << "in";
fs << "R" << R << "T" << T << "R1" << RFirst << "R2" << RSec << "P1" << PFirst << "P2" << PSec << "Q" << Q;
fs.release();
}
namedWindow("canvas", 1);
cout << "read the picture for 3d-reconstruction...";
Mat canvas(imageSize.height, imageSize.width * 2, CV_8UC3), viewLeft, viewRight;
Mat canLeft = canvas(Rect(0, 0, imageSize.width, imageSize.height));
Mat canRight = canvas(Rect(imageSize.width, 0, imageSize.width, imageSize.height));
viewLeft = imread(imageList[6], 1);//cameraIdFirst
viewRight = imread(imageList[7], 1); //cameraIdSec
viewLeft.copyTo(canLeft);
viewRight.copyTo(canRight);
cout << "done" << endl;
imshow("canvas", canvas);
waitKey(50); //必须要加waitKey ，否则可能存在无法显示图像问题
//stereoRectify
Mat rmapFirst[2], rmapSec[2], rviewFirst, rviewSec;
initUndistortRectifyMap(intrMatFirst, distCoeffsFirst, RFirst, PFirst,
imageSize, CV_16SC2, rmapFirst[0], rmapFirst[1]);//CV_16SC2
initUndistortRectifyMap(intrMatSec, distCoffesSec, RSec, PSec,//CV_16SC2
imageSize, CV_16SC2, rmapSec[0], rmapSec[1]);
remap(viewLeft, rviewFirst, rmapFirst[0], rmapFirst[1], INTER_LINEAR);
imshow("remap", rviewFirst);
waitKey(40);
remap(viewRight, rviewSec, rmapSec[0], rmapSec[1], INTER_LINEAR);
rviewFirst.copyTo(canLeft);
rviewSec.copyTo(canRight);
//rectangle(canLeft, validRoi[0], Scalar(255, 0, 0), 3, 8);
//rectangle(canRight, validRoi[1], Scalar(255, 0, 0), 3, 8);
Mat before_rectify = imread("./picture/total_0.png");
for (int j = 0; j <= canvas.rows; j += 16) //画绿线
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
for (int j = 0; j <= canvas.rows; j += 16) //画绿线
line(before_rectify, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
cout << "stereo rectify done" << endl;
imshow("校正前", before_rectify); //显示画绿线的校正后图像
imshow("校正后", canvas); //显示画绿线的校正前图像
waitKey(400000);//必须要加waitKey ，否则可能存在无法显示图像问题
return 0;
} 三、标定板
