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一种基于相位靶标的相机标定迭代畸变补偿算法

An Iterative Distortion Compensation Algorithm for Camera Calibration Based on Phase Target.

作者信息

Xu Yongjia, Gao Feng, Ren Hongyu, Zhang Zonghua, Jiang Xiangqian

机构信息

EPSRC Center, University of Huddersfield, Huddersfield HD1 3DH, UK.

School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China.

出版信息

Sensors (Basel). 2017 May 23;17(6):1188. doi: 10.3390/s17061188.

Abstract

Camera distortion is a critical factor affecting the accuracy of camera calibration. A conventional calibration approach cannot satisfy the requirement of a measurement system demanding high calibration accuracy due to the inaccurate distortion compensation. This paper presents a novel camera calibration method with an iterative distortion compensation algorithm. The initial parameters of the camera are calibrated by full-field camera pixels and the corresponding points on a phase target. An iterative algorithm is proposed to compensate for the distortion. A 2D fitting and interpolation method is also developed to enhance the accuracy of the phase target. Compared to the conventional calibration method, the proposed method does not rely on a distortion mathematical model, and is stable and effective in terms of complex distortion conditions. Both the simulation work and experimental results show that the proposed calibration method is more than 100% more accurate than the conventional calibration method.

摘要

相机畸变是影响相机校准精度的关键因素。由于畸变补偿不准确,传统的校准方法无法满足对校准精度要求较高的测量系统的需求。本文提出了一种具有迭代畸变补偿算法的新型相机校准方法。相机的初始参数通过全场相机像素和相位目标上的对应点进行校准。提出了一种迭代算法来补偿畸变。还开发了一种二维拟合和插值方法来提高相位目标的精度。与传统校准方法相比,该方法不依赖于畸变数学模型,在复杂畸变条件下稳定有效。仿真工作和实验结果均表明,所提出的校准方法比传统校准方法的精度高出100%以上。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f604/5490696/c53c2458a733/sensors-17-01188-g001.jpg

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