图像处理---标定代码
#define _GNU_SOURCE
#include “opencv2/core/core.hpp”
#include “opencv2/imgproc/imgproc.hpp”
#include “opencv2/calib3d/calib3d.hpp”
#include “opencv2/highgui/highgui.hpp”
#include “opencv2/contrib/contrib.hpp”
#include
#include
#include
#include
#include
#include
#include
#include
#include
using namespace cv;
using namespace std;
void main()
{
int i_imWrite = 0;
ifstream fin(“calibdata.txt”); /* 标定所用图像文件的路径 /
ofstream fout(“caliberation_result.txt”); / 保存标定结果的文件 /
//读取每一幅图像，从中提取出角点，然后对角点进行亚像素精确化
Mat img;
//img = imread(“left01.jpg”);
//cout << “hello”;
//imshow(“XIAORUN”, img);
cout << “开始提取角点………………” << endl;
int image_count = 0; / 图像数量 /
Size image_size; / 图像的尺寸 /
Size board_size = Size(8, 7); / 标定板上每行、列的角点数 /
vector image_points_buf; / 缓存每幅图像上检测到的角点 /
vector
string filename;
string filename_head;
int count = 0;//用于存储角点个数。
while (getline(fin, filename))
{
image_count++;
// 用于观察检验输出
cout << "image_count = " << image_count << endl;
Mat imageInput = imread(filename);
cout << "filename = " << filename << endl;
//imageInput.empty();
//imshow(“xiaorun”, filename);
//if (image_count == 1) //读入第一张图片时获取图像宽高信息
//{
image_size.width = imageInput.cols;
image_size.height = imageInput.rows;
cout << "image_size.width = " << image_size.width << endl;
cout << "image_size.height = " << image_size.height << endl;
//}
/* 提取角点 */
if (findChessboardCorners(imageInput, board_size, image_points_buf) == 0)
{
cout << "can not find chessboard corners!\n" << endl; //找不到角点
printf("error");
exit(1);
}
else
{
i_imWrite += 1;
/* 输出检验角点*/
//count++;
cout << "angular point = " << image_points_buf.size() << endl;
cout << "angular point site = " << image_points_buf << endl << endl << endl;
Mat view_gray;
cvtColor(imageInput, view_gray, CV_RGB2GRAY);
/* 亚像素精确化 */
find4QuadCornerSubpix(view_gray, image_points_buf, Size(11, 11)); //对粗提取的角点进行精确化
image_points_seq.push_back(image_points_buf); //保存亚像素角点
/* 在图像上显示角点位置 */
drawChessboardCorners(view_gray, board_size, image_points_buf, true); //用于在图片中标记角点
imshow("Camera Calibration", view_gray);//显示图片
//截取图片名字，把.jpf分离出来
for (int i = 0; i < 100; i++)
{
if (filename[i] != '.')
{
filename_head += (filename[i]);
}
else
{
break;
}
}
string filename_write = (filename_head + '_' + to_string(i_imWrite)).append(".jpg");
imwrite(filename_write, view_gray);
//printf("world");
waitKey(500);//暂停0.5S
filename_write = ' ';
filename_head = ' ';
}
}
int total = image_points_seq.size();
cout << "image_points_seq_Total = " << total << endl;
int CornerNum = board_size.width*board_size.height; //每张图片上总的角点数
/*for (int ii = 0; ii 第 " << j << "图片的数据 --> : " << endl;
}
if (0 == ii % 3) // 此判断语句，格式化输出，便于控制台查看
{
cout << endl;
}
else
{
cout.width(10);
}
//输出所有的角点
cout << " -->" << image_points_seq[ii][0].x;
cout << " -->" << image_points_seq[ii][0].y;
}*/
cout << "角点提取完成！\n" << endl;
//以下是摄像机标定
cout << "开始标定………………" << endl;
/*棋盘三维信息*/
Size square_size = Size(10, 10); /* 实际测量得到的标定板上每个棋盘格的大小 */
vector > object_points; /* 保存标定板上角点的三维坐标 */
/*内外参数*/
//Mat cameraMatrix = Mat(3, 3, CV_32FC1, Scalar::all(0)); /* 摄像机内参数矩阵 */
Mat cameraMatrix = Mat(3, 3, CV_64F, Scalar::all(0)); /* 摄像机内参数矩阵 */
vector point_counts; // 每幅图像中角点的数量
Mat distCoeffs = Mat(1, 5, CV_64F, Scalar::all(0)); /* 摄像机的5个畸变系数：k1,k2,p1,p2,k3 */
vector tvecsMat; /* 每幅图像的旋转向量 */
vector rvecsMat; /* 每幅图像的平移向量 */
/* 初始化标定板上角点的三维坐标 */
int i, j, t;
for (t = 0; t tempPointSet;
for (i = 0; i image_points2; /* 保存重新计算得到的投影点 */
cout << "\t每幅图像的标定误差：\n";
fout << "每幅图像的标定误差：\n";
for (i = 0; i tempPointSet = object_points[i];
/* 通过得到的摄像机内外参数，对空间的三维点进行重新投影计算，得到新的投影点 */
projectPoints(tempPointSet, rvecsMat[i], tvecsMat[i], cameraMatrix, distCoeffs, image_points2);
/* 计算新的投影点和旧的投影点之间的误差*/
vector tempImagePoint = image_points_seq[i];
Mat tempImagePointMat = Mat(1, tempImagePoint.size(), CV_32FC2);
Mat image_points2Mat = Mat(1, image_points2.size(), CV_32FC2);
for (int j = 0; j < tempImagePoint.size(); j++)
{
image_points2Mat.at(0, j) = Vec2f(image_points2[j].x, image_points2[j].y);
tempImagePointMat.at(0, j) = Vec2f(tempImagePoint[j].x, tempImagePoint[j].y);
}
err = norm(image_points2Mat, tempImagePointMat, NORM_L2);
total_err += err /= point_counts[i];
std::cout << "第" << i + 1 << "幅图像的平均误差：" << err << "像素" << endl;
fout << "第" << i + 1 << "幅图像的平均误差：" << err << "像素" << endl;
}
std::cout << "总体平均误差：" << total_err / image_count << "像素" << endl;
fout << "总体平均误差：" << total_err / image_count << "像素" << endl << endl;
std::cout << "评价完成！" << endl;
//保存定标结果
std::cout << "开始保存定标结果………………" << endl;
Mat rotation_matrix = Mat(3, 3, CV_32FC1, Scalar::all(0)); /* 保存每幅图像的旋转矩阵 */
fout << "相机内参数矩阵：" << endl;
fout << cameraMatrix << endl << endl;
fout << "畸变系数：\n";
fout << distCoeffs << endl << endl << endl;
for (int i = 0; i }