基于直线检测的棋盘格角点自动提取

李海; 张宪民; 陈忠

doi:10.3788/OPE.20152312.3480

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基于直线检测的棋盘格角点自动提取

信息科学 | 更新时间：2020-08-13

- 基于直线检测的棋盘格角点自动提取
- Automatic corner detection of checkerboard based on LSD
- 光学精密工程 2015年23卷第12期页码：3480-3489
- 作者机构：
  
  华南理工大学广东省精密装备与制造技术实验室,广东广州,510640
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.U1501247)();广东省科技攻关项目(No.2014B090917001)();广州市科技计划项目(No.201509033000
- DOI：10.3788/OPE.20152312.3480
  中图分类号： TP391.4
- 修回日期：2015-10-12，
  
  纸质出版日期：2015-12-25
- 稿件说明：
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李海, 张宪民, 陈忠. 基于直线检测的棋盘格角点自动提取[J]. 光学精密工程, 2015,23(12): 3480-3489

LI Hai, ZHANG Xian-min, CHEN Zhong. Automatic corner detection of checkerboard based on LSD[J]. Editorial Office of Optics and Precision Engineering, 2015,23(12): 3480-3489
李海, 张宪民, 陈忠. 基于直线检测的棋盘格角点自动提取[J]. 光学精密工程, 2015,23(12): 3480-3489 DOI： 10.3788/OPE.20152312.3480.

LI Hai, ZHANG Xian-min, CHEN Zhong. Automatic corner detection of checkerboard based on LSD[J]. Editorial Office of Optics and Precision Engineering, 2015,23(12): 3480-3489 DOI： 10.3788/OPE.20152312.3480.

摘要

针对现有棋盘格角点自动提取算法鲁棒性不足的缺点

提出了使用直线检测算法(LSD)来进行角点的自动提取。首先

使用LSD算法对标定图像进行处理

得出包含棋盘格子边缘的所有直线

并分别对所得直线的长度和角度进行伪排序以去除伪格子边缘。然后

对剩余直线的边缘端点进行近邻合并

得到角点的初始坐标并进行亚像素优化。最后

使用能量法对角点进行棋盘格结构复原与排序。实验结果显示:该方法可以正确提取含有阴影和噪声的玻璃材质标定板图像中的角点。与改进的Harris方法的角点坐标提取精度对比试验得到其最大偏差小于0.2 pixel

平均偏差小于0.15 pixel

表明该方法具有较高的鲁棒性且定位精度与改进的Harris方法相当

可用于工程实际中环境光源变化较大的场合。

Abstract

To improve the robustness of current automatic corner detection algorithms

a novel algorithm based on Line Segment Detection( LSD ) was proposed to extract the corners automatically. First

the LSD algorithm was used to process a checkerboard image to obtain all lines including checker edges. Then

the pseudo permutation of lengths and angles for obtained lines were done respectively to filter fake edges. Furthermore

the neighboring endpoints of the remaining lines were combined

and the coordinates of the corners were optimized with the sub-pixel algorithm. Finally

an energy method was utilized to recover the chessboard's structure and the corner points were ranked at the same time. Experimental results indicate that method proposed here automatically detects corners in images with noises and shadows. The maximum locating error and average error for the corner coordinate extraction are less than 0.2 pixels and 0.15 pixels respectively as compared with those of modified Harris method. This method has a higher robustness and its locating accuracy is almost as the modified Harris method

which shows it is suitable for a real factory environment.

关键词

Keywords

references

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