For testing I generate a grid image as matrix and again the grid points as point array:

This represents a "distorted" camera image along with some feature points. When I now undistort both the image and the grid points, I get the following result:

(Note that the fact that the "distorted" image is straight and the "undistorted" image is morphed is not the point, I'm just testing the undistortion functions with a straight test image.)

The grid image and the red grid points are totally misaligned now. I googled and found that some people forget to specify the "new camera matrix" parameter in undistortPoints but I didn't. The documentation also mentions a normalization but I still have the problem when I use the identity matrix as camera matrix. Also, in the central region it fits perfectly.

Why is this not identical, do I use something in a wrong way?

I use cv2 (4.1.0) in Python. Here is the code for testing:

import numpy as np import matplotlib.pyplot as plt import cv2 w = 401 h = 301 # helpers #-------- def plotImageAndPoints(im, pu, pv): plt.imshow(im, cmap="gray") plt.scatter(pu, pv, c="red", s=16) plt.xlim(0, w) plt.ylim(0, h) plt.show() def cv2_undistortPoints(uSrc, vSrc, cameraMatrix, distCoeffs): uvSrc = np.array([np.matrix([uSrc, vSrc]).transpose()], dtype="float32") uvDst = cv2.undistortPoints(uvSrc, cameraMatrix, distCoeffs, None, cameraMatrix) uDst = [uv[0] for uv in uvDst[0]] vDst = [uv[1] for uv in uvDst[0]] return uDst, vDst # test data #---------- # generate grid image img = np.ones((h, w), dtype = "float32") img[0::20, :] = 0 img[:, 0::20] = 0 # generate grid points uPoints, vPoints = np.meshgrid(range(0, w, 20), range(0, h, 20), indexing='xy') uPoints = uPoints.flatten() vPoints = vPoints.flatten() # see if points align with the image plotImageAndPoints(img, uPoints, vPoints) # perfect! # undistort both image and points individually #--------------------------------------------- # camera matrix parameters fx = 1 fy = 1 cx = w/2 cy = h/2 # distortion parameters k1 = 0.00003 k2 = 0 p1 = 0 p2 = 0 # convert for opencv mtx = np.matrix([ [fx, 0, cx], [ 0, fy, cy], [ 0, 0, 1] ], dtype = "float32") dist = np.array([k1, k2, p1, p2], dtype = "float32") # undistort image imgUndist = cv2.undistort(img, mtx, dist) # undistort points uPointsUndist, vPointsUndist = cv2_undistortPoints(uPoints, vPoints, mtx, dist) # test if they still match plotImageAndPoints(imgUndist, uPointsUndist, vPointsUndist) # awful!

Any help appreciated!