<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>On the basis of studying the calibration method of the camera and the rotating platform, we designed an automatic camera calibration scheme based on four azimuth circles, which can realize the automatic sorting of the mark points. In order to improve the efficiency of identifying the center of the calibration plate, this paper uses RANSAC to improve the RED ellipse center detection algorithm. Experimental verification shows that the improved RED algorithm has increased 29.34% in anti-noise interference ability and 30.10% in center detection accuracy, which effectively guarantees the measurement stability and accuracy of the measurement system. Then, with the aid of the designed calibration board, we fit the rotation center of the turntable using the principle of three points in a circle, which provides a basis for the subsequent point cloud splicing. Experiments show that the back-projection error of the calibration method in this paper is less than 1 pixel, and the calibration accuracy is better than Zhang’s algorithm.</p>
</abstract>

On the basis of studying the calibration method of the camera and the rotating platform, we designed an automatic camera calibration scheme based on four azimuth circles, which can realize the automatic sorting of the mark points. In order to improve the efficiency of identifying the center of the calibration plate, this paper uses RANSAC to improve the RED ellipse center detection algorithm. Experimental verification shows that the improved RED algorithm has increased 29.34% in anti-noise interference ability and 30.10% in center detection accuracy, which effectively guarantees the measurement stability and accuracy of the measurement system. Then, with the aid of the designed calibration board, we fit the rotation center of the turntable using the principle of three points in a circle, which provides a basis for the subsequent point cloud splicing. Experiments show that the back-projection error of the calibration method in this paper is less than 1 pixel, and the calibration accuracy is better than Zhang’s algorithm.

Calibration of Structured Light Scanning System

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Calibration of Structured Light Scanning System"}

On the basis of studying the calibration method of the camera and the rotating platform, we designed an automatic camera calibration scheme based on four...

Group	e_a	e_m
1	0.191	0.650
2	0.177	0.801
3	0.266	0.502

Name	Average measurement result of this system	Measurement standard deviation	LJ-V7000measurement results
Arch length	63.87	0.10	63.91
Arch width	58.02	0.12	58.03
41 teeth	5.58	0.12	5.63
42 teeth	6.52	0.09	6.45
43 teeth	7.28	0.11	7.32
44 teeth	7.89	0.17	7.89
45 teeth	7.48	0.06	7.46
46 teeth	11.00	0.07	10.97
31 teeth	5.41	0.08	5.41
32 teeth	6.39	0.10	6.31
33 teeth	6.98	0.07	7.06
34 teeth	7.79	0.12	7.76
35 teeth	7.45	0.07	7.43
36 teeth	11.05	0.13	10.95

Group	e_a	e _m
1	0.613	1.124
2	0.691	2.316
3	0.827	1.528

Calibration of Structured Light Scanning System

Online veröffentlicht: 21. Feb. 2022

Seitenbereich: 56 - 64

DOI: https://doi.org/10.21307/ijanmc-2021-017

Schlüsselwörter
Camera Calibration, Point Cloud Stitching, Dental Model, Three-Dimensional Measurement

© 2021 Yi Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Figure 10.

THE BACK PROJECTION ERROR RESULTS OF THE ALGORITHM

MEASUREMENT INFORMATION OF DENTAL MODEL (UNIT: MM)

BACK-PROJECTION ERROR RESULTS OF ZHANG'S CALIBRATION METHOD

Calibration of Structured Light Scanning System

Online veröffentlicht: 21. Feb. 2022

Seitenbereich: 56 - 64

DOI: https://doi.org/10.21307/ijanmc-2021-017

SchlüsselwörterCamera Calibration, Point Cloud Stitching, Dental Model, Three-Dimensional Measurement

© 2021 Yi Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Figure 10.

THE BACK PROJECTION ERROR RESULTS OF THE ALGORITHM

MEASUREMENT INFORMATION OF DENTAL MODEL (UNIT: MM)

BACK-PROJECTION ERROR RESULTS OF ZHANG'S CALIBRATION METHOD

Schlüsselwörter
Camera Calibration, Point Cloud Stitching, Dental Model, Three-Dimensional Measurement