Calibration of Structured Light Scanning System

Yi Guo, Xiaoyi Ruan
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Abstract

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.
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结构光扫描系统的标定
摘要在研究摄像机与旋转平台标定方法的基础上,设计了一种基于四个方位角圆的摄像机自动标定方案,实现了标记点的自动分选。为了提高标定板中心的识别效率,本文采用RANSAC对RED椭圆中心检测算法进行改进。实验验证表明,改进后的RED算法抗噪声干扰能力提高29.34%,中心检测精度提高30.10%,有效地保证了测量系统的测量稳定性和精度。然后,借助所设计的标定板,利用三点一圆的原理对转台的旋转中心进行拟合,为后续的点云拼接提供基础。实验表明,本文标定方法的反投影误差小于1个像素,标定精度优于Zhang算法。
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