【计算机视觉】相机畸变校正（Lens Distortion Correction）

#!/usr/bin/env python

import cv2
import numpy as np
import os
import glob

# Defining the dimensions of checkerboard
CHECKERBOARD = (6,9)
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# Creating vector to store vectors of 3D points for each checkerboard image
objpoints = []
# Creating vector to store vectors of 2D points for each checkerboard image
imgpoints = [] 


# Defining the world coordinates for 3D points
objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)
objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
prev_img_shape = None

# Extracting path of individual image stored in a given directory
images = glob.glob('./images/*.jpg')
for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    # Find the chess board corners
    # If desired number of corners are found in the image then ret = true
    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE)
    
    """
    If desired number of corner are detected,
    we refine the pixel coordinates and display 
    them on the images of checker board
    """
    if ret == True:
        objpoints.append(objp)
        # refining pixel coordinates for given 2d points.
        corners2 = cv2.cornerSubPix(gray, corners, (11,11),(-1,-1), criteria)
        
        imgpoints.append(corners2)

        # Draw and display the corners
        img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)
    
    cv2.imshow('img',img)
    cv2.waitKey(0)

cv2.destroyAllWindows()

h,w = img.shape[:2]

"""
Performing camera calibration by 
passing the value of known 3D points (objpoints)
and corresponding pixel coordinates of the 
detected corners (imgpoints)
"""
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)

print("Camera matrix : n")
print(mtx)
print("dist : n")
print(dist)
print("rvecs : n")
print(rvecs)
print("tvecs : n")
print(tvecs)　

#include <opencv2/opencv.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <stdio.h>
#include <iostream>

// Defining the dimensions of checkerboard
int CHECKERBOARD[2]{6,9}; 

int main()
{
  // Creating vector to store vectors of 3D points for each checkerboard image
  std::vector<std::vector<cv::Point3f> > objpoints;

  // Creating vector to store vectors of 2D points for each checkerboard image
  std::vector<std::vector<cv::Point2f> > imgpoints;

  // Defining the world coordinates for 3D points
  std::vector<cv::Point3f> objp;
  for(int i{0}; i<CHECKERBOARD[1]; i++)
  {
    for(int j{0}; j<CHECKERBOARD[0]; j++)
      objp.push_back(cv::Point3f(j,i,0));
  }


  // Extracting path of individual image stored in a given directory
  std::vector<cv::String> images;
  // Path of the folder containing checkerboard images
  std::string path = "./images/*.jpg";

  cv::glob(path, images);

  cv::Mat frame, gray;
  // vector to store the pixel coordinates of detected checker board corners 
  std::vector<cv::Point2f> corner_pts;
  bool success;

  // Looping over all the images in the directory
  for(int i{0}; i<images.size(); i++)
  {
    frame = cv::imread(images[i]);
    cv::cvtColor(frame,gray,cv::COLOR_BGR2GRAY);

    // Finding checker board corners
    // If desired number of corners are found in the image then success = true  
    success = cv::findChessboardCorners(gray, cv::Size(CHECKERBOARD[0], CHECKERBOARD[1]), corner_pts, CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FAST_CHECK | CV_CALIB_CB_NORMALIZE_IMAGE);
    
    /* 
     * If desired number of corner are detected,
     * we refine the pixel coordinates and display 
     * them on the images of checker board
    */
    if(success)
    {
      cv::TermCriteria criteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 30, 0.001);
      
      // refining pixel coordinates for given 2d points.
      cv::cornerSubPix(gray,corner_pts,cv::Size(11,11), cv::Size(-1,-1),criteria);
      
      // Displaying the detected corner points on the checker board
      cv::drawChessboardCorners(frame, cv::Size(CHECKERBOARD[0], CHECKERBOARD[1]), corner_pts, success);
      
      objpoints.push_back(objp);
      imgpoints.push_back(corner_pts);
    }

    cv::imshow("Image",frame);
    cv::waitKey(0);
  }

  cv::destroyAllWindows();

  cv::Mat cameraMatrix,distCoeffs,R,T;

  /*
   * Performing camera calibration by 
   * passing the value of known 3D points (objpoints)
   * and corresponding pixel coordinates of the 
   * detected corners (imgpoints)
  */
  cv::calibrateCamera(objpoints, imgpoints, cv::Size(gray.rows,gray.cols), cameraMatrix, distCoeffs, R, T);

  std::cout << "cameraMatrix : " << cameraMatrix << std::endl;
  std::cout << "distCoeffs : " << distCoeffs << std::endl;
  std::cout << "Rotation vector : " << R << std::endl;
  std::cout << "Translation vector : " << T << std::endl;

  return 0;
}

# Refining the camera matrix using parameters obtained by calibration
newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w,h), 1, (w,h))

# Method 1 to undistort the image
dst = cv2.undistort(img, mtx, dist, None, newcameramtx)

# Method 2 to undistort the image
mapx,mapy=cv2.initUndistortRectifyMap(mtx,dist,None,newcameramtx,(w,h),5)

dst = cv2.remap(img,mapx,mapy,cv2.INTER_LINEAR)

# Displaying the undistorted image
cv2.imshow("undistorted image",dst)
cv2.waitKey(0)

cv::Mat dst, map1, map2,new_camera_matrix;
cv::Size imageSize(cv::Size(image.cols,image.rows));

// Refining the camera matrix using parameters obtained by calibration
new_camera_matrix = cv::getOptimalNewCameraMatrix(cameraMatrix, distCoeffs, imageSize, 1, imageSize, 0);

// Method 1 to undistort the image
cv::undistort( frame, dst, new_camera_matrix, distCoeffs, new_camera_matrix );

// Method 2 to undistort the image
cv::initUndistortRectifyMap(cameraMatrix, distCoeffs, cv::Mat(),cv::getOptimalNewCameraMatrix(cameraMatrix, distCoeffs, imageSize, 1, imageSize, 0),imageSize, CV_16SC2, map1, map2);

cv::remap(frame, dst, map1, map2, cv::INTER_LINEAR);

//Displaying the undistorted image
cv::imshow("undistorted image",dst);
cv::waitKey(0);;