利用圆心不对称投影精确标定工业相机

朱伟东; 曹良洪; 梅标; 李江雄; 封璞加

doi:10.3788/OPE.20142208.2267

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利用圆心不对称投影精确标定工业相机

信息科学 | 更新时间：2020-08-13

- 利用圆心不对称投影精确标定工业相机
- Calibration of industrial cameras using asymmetric circle center projection
- 光学精密工程 2014年22卷第8期页码：2267-2273
- 作者机构：
  
  1. 浙江大学机械工程学院系,浙江杭州,310027
  2. 中国航空工业集团公司陕西飞机工业（集团）有限公司,陕西汉中,723213
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（No.51205352）()
- DOI：10.3788/OPE.20142208.2267
  中图分类号： TB853;TP391
- 收稿日期：2013-11-29，
  
  修回日期：2014-01-04，
  
  纸质出版日期：2014-08-25
- 稿件说明：
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朱伟东, 曹良洪, 梅标等. 利用圆心不对称投影精确标定工业相机[J]. 光学精密工程, 2014,22(8): 2267-2273

ZHU Wei-dong, CAO Liang-hong, MEI Biao etc. Calibration of industrial cameras using asymmetric circle center projection[J]. Editorial Office of Optics and Precision Engineering, 2014,22(8): 2267-2273
朱伟东, 曹良洪, 梅标等. 利用圆心不对称投影精确标定工业相机[J]. 光学精密工程, 2014,22(8): 2267-2273 DOI： 10.3788/OPE.20142208.2267.

ZHU Wei-dong, CAO Liang-hong, MEI Biao etc. Calibration of industrial cameras using asymmetric circle center projection[J]. Editorial Office of Optics and Precision Engineering, 2014,22(8): 2267-2273 DOI： 10.3788/OPE.20142208.2267.

摘要

工业相机常采用基于圆形控制点的方法进行标定，但该方法存在不对称投影问题，极易产生标定误差。为了避免引入不对称投影误差并能以迭代方式修正这一误差，本文提出了一种利用圆心不对称投影所蕴含信息的相机标定方法。首先，推导了平面模板上的圆形控制点投影成为椭圆之后的理论坐标；然后，提取每一幅标定板图像中实际椭圆的中心坐标，通过最小二乘算法求得该幅图像对应的精确投影变换矩阵；最后，利用所有的投影变换矩阵求出相机内参数。实验结果表明：采用本文提出的标定方法，标定结果的重投影误差降到了1/50 pixel。该方法可一次完成标定，计算简单，标定精度高，适用于工业相机的标定。

Abstract

The calibration of industrial cameras usually uses circular points as control points. However

there is asymmetric projection in the calibration

so that the calibration results have errors. In order to avoid the introduction of asymmetric projection error and to correct the error in an iteration form

this paper proposes a new camera calibration method by utilizing the asymmetric projection of circular centers. Firstly

the theoretical coordinate of the projection ellipse center from a circular point on the planar pattern was deduced

then the center coordinate of actual ellipse for the image of a calibration board was extracted and the projective transformation matrix was obtained by using nonlinear least square method. Finally

the camera intrinsic parameters were obtained by using all projective transformation matrixes. Experimental result reveals that the re-projection error of the calibration result of Baumer TXG12 industrial camera is just about 1/50 pixels by using proposed method. The method can complete the calibration at a time and is able to meet the precision requirement of industrial measurement in simpler calculation and higher accuracy.

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references

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