标定板的质量对标定精度影响也是非常大的,我手上有一个陶瓷的Halcon原点标定板,使用Halcon标定效果很好。但由于想转用OpenCV开发,且不想放弃已有的图像数据,因此想将Halcon标定的数据(内参、外参,畸变系数),转换到OpenCV中。
当然,其参数不是一一对应的(也就是说,Halcon中的畸变系数与OpenCV中的畸变系数并不一一对应,按照官方的说法是其求解的畸变参数的形式是不一样的。一个是由校正前到校正后求解得到,一个是由校正后到校正前求解得到)。
依据Stack Overflow中的数据,写了一个转换的类,输入Halcon中的标定数据,就可以得到OpenCV中的参数,可以实现校正畸变,具体精度还有待进一步研究。
源地址:https://stackoverflow.com/questions/58606394/halcon-to-opencv-distortion-coefficients-convertion/58991972#58991972
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更正:第一版中畸变计算出现错误(低级错误),内参矩阵误乘了一个尺度因子。
OpenCV中的畸变参数排列为 K1 K2 P1 P2 K3(Halcon中是 K1 K2 K3 P1 P2)大坑啊!
k 1 o p e n c v = k 1 h a l c o n ∗ f m m ∗ f m m ; k 2 o p e n c v = k 2 h a l c o n ∗ f m m ∗ f m m ∗ f m m ∗ f m m ; k 3 o p e n c v = k 3 h a l c o n ∗ f m m ∗ f m m ∗ f m m ∗ f m m ∗ f m m ∗ f m m ; p 1 o p e n c v = p 2 h a l c o n ∗ f m m ; ( 注 意 这 里 是 p 2 ) p 2 o p e n c v = p 1 h a l c o n ∗ f m m ; \begin{aligned} k1_{opencv} &= k1_{halcon} * fmm * fmm; \\ k2_{opencv} &= k2_{halcon} * fmm * fmm * fmm * fmm; \\ k3_{opencv} &= k3_{halcon} * fmm * fmm * fmm * fmm * fmm * fmm; \\ p1_{opencv} &= p2_{halcon} * fmm; (注意这里是p_{2}) \\ p2_{opencv} &= p1_{halcon} * fmm; \\ \end{aligned} k1opencvk2opencvk3opencvp1opencvp2opencv=k1halcon∗fmm∗fmm;=k2halcon∗fmm∗fmm∗fmm∗fmm;=k3halcon∗fmm∗fmm∗fmm∗fmm∗fmm∗fmm;=p2halcon∗fmm;(注意这里是p2)=p1halcon∗fmm;
f m m fmm fmm指代焦距Focal Length。
* 读取参数模型
read_camera_setup_model ('stereo_camera_setupOpenCV.csm', CameraSetupModelID)
get_camera_setup_param (CameraSetupModelID, 0, 'params', CamParam0) // 提取相机的内参数
get_cam_par_data (CamParam0, 'focus', focus0) // 焦距
get_cam_par_data (CamParam0, 'sx', sx0) // Sx 像元尺寸
get_cam_par_data (CamParam0, 'sy', sy0) // Sy 像元尺寸
get_cam_par_data (CamParam0, 'cx', cx0) // 主点坐标 cx
get_cam_par_data (CamParam0, 'cy', cy0) // 主点坐标 cy
get_cam_par_data (CamParam0, 'k1', k10) // 畸变系数
get_cam_par_data (CamParam0, 'k2', k20) // 畸变系数
get_cam_par_data (CamParam0, 'k3', k30) // 畸变系数
get_cam_par_data (CamParam0, 'p1', p10) // 畸变系数
get_cam_par_data (CamParam0, 'p2', p20) // 畸变系数
change_radial_distortion_cam_par ('adaptive', CamParam0, [0,0,0,0,0], CamParamOut) // 为了生成内参矩阵
cam_par_to_cam_mat (CamParamOut, CamParam0Out, ImageWidth, ImageHeight) // 内参矩阵
* ** 外参数
* 0号相机
get_camera_setup_param (CameraSetupModelID, 0, 'pose', Pose3)
pose_to_hom_mat3d (Pose3, HomMat3D_0)
其实,setcameraMatrix_Halcon没什么用,可以不用添加。
设置参数并测试
//
// Created by zzl on 10/21/20.
//
#include
#include "opencv2/opencv.hpp"
#include "ParamsConvert.h" // 转化用的头文件
using namespace std;
using namespace cv;
int main(int argc,char** argv) {
CameraParams camera0; // 声明类
camera0.setcameraMatrix_Halcon(2284.79, 2273.73, 444.25, 579.716); // 导入参数,这个函数没什么用
camera0.setcameraParams_Halcon(0.00861914, 3.75142e-06, 3.75e-06, 445.868, 582.908); // 导入Halcon中的数据,内参
camera0.setcameraDistCoeffs_Halcon(954.86, 2.8045e+08, -2.35577e+13, 0.451309, 0.457282); // 导入Halcon中的数据,畸变系数(5参数,注意p2,p1位置交换了)
camera0.setcameraRotation(0.0808079, 0.0137326, 0.996635, 0.996676, -0.0114733, -0.0806531, 0.0103271, 0.99984,
-0.0146141); // 导入Halcon中的数据,旋转矩阵
camera0.setcameraTranspose(-0.129098 , -0.00118334 , 0.122701 ); // 导入Halcon中的数据,平移向量(注意单位)
// Camera0
// Read Image and Test
Mat src_0 = imread("./0-0.bmp", 1);
namedWindow("Input_0", WINDOW_NORMAL);
imshow("Input_0", src_0);
// Convert Params
camera0.Halcon2OpenCV();
Mat cameraMatrix0_OpenCV = camera0.cameraMatrix_OpenCV; // 读取类中的内参矩阵
Mat cameraDist0_OpenCV = camera0.distCoeffs_OpenCV; // 读取类中的畸变矩阵
Mat dst_0;
undistort(src_0, dst_0, cameraMatrix0_OpenCV, cameraDist0_OpenCV, noArray());
namedWindow("Output_0", WINDOW_NORMAL);
imshow("Output_0", dst_0);
waitKey();
cout<<"Hello World"<<endl;
return 0;
}
// header
// Created by zzl on 10/20/20.
//
#include "opencv2/opencv.hpp"
#include "opencv2/calib3d.hpp"
#ifndef HALCONPARAMS2OPENCV_PARAMSCONVERT_H
#define HALCONPARAMS2OPENCV_PARAMSCONVERT_H
class CameraParams {
// 转换畸变系数
public:
void Halcon2OpenCV();
void setcameraMatrix_Halcon(float fx,float fy,float cx,float cy); // 导入Halcon中的数据
void setcameraParams_Halcon(float focal_Halcon,float sx_Halcon,float sy_Halcon,float Cx,float Cy); // 导入Halcon中的数据
void setcameraDistCoeffs_Halcon(float k1,float k2,float k3,float p2,float p1); // 导入Halcon中的数据,注意畸变系数p1、p2
void setcameraRotation(float x1,float x2,float x3,float y1,float y2,float y3,float z1,float z2,float z3); // 设置旋转矩阵
void setcameraTranspose(float t1,float t2,float t3); // 设置平移矩阵
cv::Mat cameraMatrix_OpenCV = cv::Mat::zeros(3, 3, CV_32F); // 输出的相机内参矩阵
cv::Mat distCoeffs_OpenCV = cv::Mat::zeros(1, 5, CV_32F); // 输出的相机畸变系数
cv::Mat cameraRotation= cv::Mat::zeros(3,3,CV_32F); // 输出的相机旋转矩阵
cv::Mat cameraTrans = cv::Mat::zeros(3,1,CV_32F); // 输出的相机平移向量
private:
// 定义Halcon的基本参数
cv::Mat cameraMatrix_Halcon = cv::Mat::zeros(3, 3, CV_32F);
cv::Mat distCoeffs_Halcon = cv::Mat::zeros(1, 5, CV_32F); // 以k1,k2,k3,p2,p1
double focal_Halcon, sx_Halcon, sy_Halcon, Cx, Cy;
};
// 函数实现
void CameraParams::Halcon2OpenCV() {
//cv::Mat OpenCVMatrix = cv::Mat::zeros(1,5,CV_32F);
// DistCoeffs
distCoeffs_OpenCV.at<float>(0, 0) = distCoeffs_Halcon.at<float>(0, 0) * focal_Halcon * focal_Halcon; // K1
distCoeffs_OpenCV.at<float>(0, 1) =
distCoeffs_Halcon.at<float>(0, 1) * focal_Halcon * focal_Halcon * focal_Halcon * focal_Halcon; // K2
distCoeffs_OpenCV.at<float>(0, 4) =
distCoeffs_Halcon.at<float>(0, 2) * focal_Halcon * focal_Halcon * focal_Halcon * focal_Halcon *
focal_Halcon * focal_Halcon; // K3为OpenCV畸变中的最后一个
// P1
distCoeffs_OpenCV.at<float>(0, 2) = distCoeffs_Halcon.at<float>(0, 3) * focal_HalconMM; // P2
distCoeffs_OpenCV.at<float>(0, 3) = distCoeffs_Halcon.at<float>(0, 4) * focal_HalconMM; // P1
// CameraMatrix
cameraMatrix_OpenCV.at<float>(0, 0) = (focal_Halcon / sx_Halcon) ; // 尺度因子 focal_Halcon单位为mm,Sx_Halcon为 mm/像素 注意单位 mm还是um
cameraMatrix_OpenCV.at<float>(0, 1) = 0.0;
cameraMatrix_OpenCV.at<float>(0, 2) = Cx;
cameraMatrix_OpenCV.at<float>(1, 0) = 0.0;
cameraMatrix_OpenCV.at<float>(1, 1) = (focal_Halcon / sy_Halcon) ;
cameraMatrix_OpenCV.at<float>(1, 2) = Cy;
cameraMatrix_OpenCV.at<float>(2, 0) = 0.0;
cameraMatrix_OpenCV.at<float>(2, 1) = 0.0;
cameraMatrix_OpenCV.at<float>(2, 2) = 1.0;
}
void CameraParams::setcameraMatrix_Halcon(float fx,float fy,float cx,float cy){
cameraMatrix_Halcon.at<float>(0,0) = fx;
cameraMatrix_Halcon.at<float>(0,2) = cx;
cameraMatrix_Halcon.at<float>(1,1) = fy;
cameraMatrix_Halcon.at<float>(1,3) = cy;
}
void CameraParams::setcameraParams_Halcon(float focal_HalconIN, float sx_HalconIN, float sy_HalconIN, float CxIN, float CyIN) {
focal_Halcon = focal_HalconIN;
sx_Halcon = sx_HalconIN;
sy_Halcon = sy_HalconIN;
Cx = CxIN;
Cy = CyIN;
}
void CameraParams::setcameraDistCoeffs_Halcon(float k1, float k2, float k3, float p2, float p1) {
distCoeffs_Halcon.at<float>(0,0) = k1;
distCoeffs_Halcon.at<float>(0,1) = k2;
distCoeffs_Halcon.at<float>(0,2) = k3;
distCoeffs_Halcon.at<float>(0,3) = p2;
distCoeffs_Halcon.at<float>(0,4) = p1;
}
void CameraParams::setcameraRotation(float x1,float x2,float x3,float y1,float y2,float y3,float z1,float z2,float z3){
cameraRotation.at<float>(0,0) = x1;
cameraRotation.at<float>(0,1) = x2;
cameraRotation.at<float>(0,2) = x3;
cameraRotation.at<float>(1,0) = y1;
cameraRotation.at<float>(1,1) = y2;
cameraRotation.at<float>(1,2) = y3;
cameraRotation.at<float>(2,0) = z1;
cameraRotation.at<float>(2,1) = z2;
cameraRotation.at<float>(2,2) = z3;
}
void CameraParams::setcameraTranspose(float t1, float t2, float t3) {
cameraTrans.at<float>(0,0) = t1;
cameraTrans.at<float>(1,0) = t2;
cameraTrans.at<float>(2,0) = t3;
}
#endif //HALCONPARAMS2OPENCV_PARAMSCONVERT_H
cmake_minimum_required(VERSION 3.10)
project(HalconParams2OpenCV)
set(CMAKE_CXX_STANDARD 14)
find_package(OpenCV REQUIRED)
message(STATUS "OpenCV Version:\t " ${
OpenCV_VERSION})
include_directories(${
OpenCV_INCLUDES})
add_executable(HalconParams2OpenCV main.cpp ParamsConvert.h )
target_link_libraries(HalconParams2OpenCV ${
OpenCV_LIBS} )
具体精度有待进一步研究!~