基于改进棋盘的角点自动检测与排序

赵斌; 周军

doi:10.3788/OPE.20152301.0237

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基于改进棋盘的角点自动检测与排序

信息科学 | 更新时间：2020-08-13

- 基于改进棋盘的角点自动检测与排序
- Automatic detection and sorting of corners by improved chessboard pattern
- 光学精密工程 2015年23卷第1期页码：237-244
- 作者机构：
  
  西北工业大学精确制导与控制研究所,陕西西安,710072
- 作者简介：
  
  [ "赵斌(1986-), 男, 陕西周至人, 博士, 讲师, 2007年, 2011年于西北工业大学航天学院分别获得学士、博士学位, 主要从事飞行器制导控制及半实物仿真方面的研究.E-mail:b.zhao_npu@hotmial.com" ]
  [ "周军(1966-), 男, 江苏常州人, 博士, 教授, 博士生导师, 1988年, 1993年于西北工业大学分别获得学士、博士学位, 1995年于中国空间技术研究院一站博士后出站, 1997年于西北工业大学二站博士后出站, 现为陕西省微小卫星工程实验室主任, 主要从事飞行器制导控制及先进控制理论的研究.E-mail:Zhoujun@nwpu.edu.cn" ]
- 基金信息：
  
  西北工业大学基础研究基金资助项目(No.JCT20130101)()
- DOI：10.3788/OPE.20152301.0237
  中图分类号： TP391.4
- 收稿日期：2014-05-13，
  
  修回日期：2014-06-23，
  
  纸质出版日期：2015-01-25
- 稿件说明：
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赵斌, 周军,. 基于改进棋盘的角点自动检测与排序[J]. 光学精密工程, 2015,23(1): 237-244

ZHAO Bin, ZHOU Jun,. Automatic detection and sorting of corners by improved chessboard pattern[J]. Editorial Office of Optics and Precision Engineering, 2015,23(1): 237-244
赵斌, 周军,. 基于改进棋盘的角点自动检测与排序[J]. 光学精密工程, 2015,23(1): 237-244 DOI： 10.3788/OPE.20152301.0237.

ZHAO Bin, ZHOU Jun,. Automatic detection and sorting of corners by improved chessboard pattern[J]. Editorial Office of Optics and Precision Engineering, 2015,23(1): 237-244 DOI： 10.3788/OPE.20152301.0237.

摘要

考虑采用传统黑白棋盘进行相机自动标定时角点排序结果受标定模板旋转角度影响较大

本文设计了一种改进的棋盘标定模板及相应的角点自动检测与排序算法.新的标定模板通过增加4个长方形边界滤除复杂背景

增加沙漏状图形确定排序原点

从而使得排序结果适应于模板的旋转.针对新的标定模板提出了一种基于对称象限灰度交叉熵的角点检测算法

该算法通过抑制局部非极大值以及筛选矩形边界实现了角点的像素级定位

然后采用Frostner算子解算了角点的亚像素坐标.针对角点检测结果

采用曲线拟合并结合角点至原点的距离信息实现了角点自动排序.实验结果表明:得到的角点检测结果正确

亚像素解算坐标与Matlab标定工具箱的检测结果误差小于0.8 pixel

排序结果对标定模板的旋转具有不变性

易于实现在线标定.

Abstract

In automatic camera calibration with traditional black and white chessboard patterns

the corner sorting results are usually influenced by the rotation angle of the calibration pattern. Therefore

this paper designs an improved chessboard pattern and corresponding automatic corner detection and sorting algorithm. In the new pattern

four rectangular boundaries were added to filter the complex background

and a double-triangle mark was used to determine the original point of the corners so as to adapt to the rotation of the pattern. A corner detection algorithm based on cross entropy of the symmetrical quadrant was proposed to implement the corner position with the accuracy of pixel level by local non-maximum suppression and rectangular selection. Then

the Frostner operator was used to calculate the sub-pixel coordinates of the corners. According to the detected corner

the curve fitting method was employed to realize the automatic corner sorting with the distance information between the corners and the origin. Experiment results show that the corner detection results are correct and the sub-pixel coordinate error between the new method and Matlab Calibration Toolbox is less than 0.8 pixel unit. Moreover

the sorting results show an invariance to the pattern rotation

which verifies that the method is suitable for online auto camera calibration.

关键词

Keywords

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