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Overview: In the past two decades, camera calibration theory has been continuously developed and improved. The calibration method based on planar two-dimensional targets has been most widely applied. In the actual calibration process, the captured target images would appear to various degrees of blurring due to environmental factors and camera focus errors. The accuracy of feature point extraction would be affected. Since the phase information is not influenced by the blur of the captured image, some scholars have proposed using a liquid crystal display panel that displays phase patterns as a calibration target. The phase code is used to establish the correspondence between feature point world coordinates and image coordinates to achieve high-precision calibration of the camera. Compared with the calibration method based on Fourier analysis, the calibration method based on phase shift theory has higher accuracy. However, its calibration process is cumbersome because multiple images need to be collected for each target pose. Furthermore, such calibration methods require human intervention when extracting feature points, that is, manually selecting four outer corner points to determine a target area for feature point extraction. The calibration process is complicated.
This paper proposes a calibration method based on the color-coded phase-shifted fringe to overcome the shortcomings of the calibration method based on phase-shifted theory. This method encoded a phase-shifted stripe through the RGB channels of a color pattern and used a liquid crystal display panel as a calibration target to sequentially display horizontal and vertical color-coded phase-shifted stripes. Through the color channel separation, orthogonal phase-shifted fringes were obtained. The intersection point of the orthogonal phase truncation line was taken as the characteristic point according to the phase-shifted theory. Applied the calibration theory based on the planar two-dimensional target, the calibration of the single-camera and binocular system was realized by changing the target pose multiple times and extracting feature points. Furthermore, calibration efficiency was improved by adding color-coded phase-shifted rings to the four corners of the target pattern to automatically extract and sort feature points. The single-camera calibration experiment shows that when the target pattern is blurred, the calibration accuracy of the method in this paper is significantly better than that of the chessboard target under the premise that the calibration target pose changes the same number of times. It is slightly higher than the orthogonal sinusoidal fringe target and slightly lower than the orthogonal sinusoidal phase-shifted fringe target. The experiment also shows that the number of pictures collected by this method is only one-third of the orthogonal sinusoidal phase-shifted fringe target. When the total number of collected pictures is the same, the reprojection error of this calibration method is the smallest and the precision is the highest. The calibration accuracy is stable under different defocusing degrees. The binocular system calibration experiment shows that the system has high measurement accuracy after calibration, and it can realize 3D reconstruction of the measured object.
Phase target based on color-coded phase-shift fringe.
Image of target.
The image after removing the background. (a) Vertical wrapped phase; (b) Horizontal wrapped phase diagram
Sorting the feature points. (a) Feature point extraction results; (b) Sorting the local points; (c) The feature points after sorting
Experimental setup
Targets captured at different distances and corresponding feature point extraction results.
Experimental setup
Left and right image of binocular stereo vision system and 3D reconstruction of chessboard corners. (a) Calibration target taken with the left camera; (b) Calibration target taken with the right camera; (c) 3D reconstruction of chessboard corners
Left and right image of binocular stereo vision system.
3D point cloud of plaster portrait.