高精度摄像机标定模板的设计及识别算法

梁力 1

您当前的位置：

首页 >

文章列表页 >

高精度摄像机标定模板的设计及识别算法

更新时间：2025-11-17

- 高精度摄像机标定模板的设计及识别算法
- Design and Detection Methods for Accurate Camera Calibration Targets
- 西安交通大学学报 2011年45卷第4期页码：82-85
- 作者机构：
  
  西安交通大学软件学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  中图分类号： TN391.4
- 纸质出版：2011
- 稿件说明：
移动端阅览
梁力 1. 高精度摄像机标定模板的设计及识别算法[J]. 西安交通大学学报, 2011,45(4):82-85.

梁力 1. Design and Detection Methods for Accurate Camera Calibration Targets[J]. 2011, 45(4): 82-85.
梁力 1. 高精度摄像机标定模板的设计及识别算法[J]. 西安交通大学学报, 2011,45(4):82-85. DOI：

梁力 1. Design and Detection Methods for Accurate Camera Calibration Targets[J]. 2011, 45(4): 82-85. DOI：

摘要

针对目前摄像机标定模板——黑白棋盘格识别精度低导致标定精度降低的问题

提出了一种以渐变圆形为特征的摄像机标定模板以及相应的检测算法. 新的摄像机标定模板以渐变圆形作为图元代替以前的棋盘格交点

从而可以使摄像机更精确地对其位置进行识别

得到更精确的摄像机标定结果

并保留了黑白棋盘格作为标定模板

具有制作简易

成本低廉的优势

并且针对这种标定模板

提出了精确的检测算法.实验结果表明

在相同的摄像机和相同的环境下

新标定模板和检测算法标定的投影误差比黑白棋盘格的标定结果减少了20%.

Abstract

A new camera calibration target and its detection method are presented to improve the low accuracy of existing common checkerboard detection methods. The new calibration target uses gradient circle as its primitive element

and thus has easy to make

cheap and more accurate features compared with the checkerboard. It is easy and accurate to detect the new designed camera calibration target since the new calibration target contains more information than common checkerboard. A more accurate detection method is provided for the new calibration target. Experimental results and comparisons with the checkboard show that the new target with the detection method reduces the projection error by 20%.

关键词

Keywords

references

YU Minglang, WEI Zhenzhong, SUN Junhu. On-spot camera calibration method based on flexible planar target [J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(3):347-350.

KIM W S, ANSAR A I, STEELE R D. Rover mast calibration, exact camera pointing, and camera handoff for visual target tracking [C]∥Proceedings of 12th International Conference on Advanced Robotics. Los Alamitos, CA,USA: IEEE Computer Society, 2005: 384-391.

CHEN Dazhi, WANG Ying, ZHANG Guangjun. A new sub-pixel detector for grid target points in camera calibration [C]∥Proc SPIE Int Soc Opt Eng. Bellingham, WA, USA: SPIE, 2006: 675-680.

AHN S J, RAUH W, KIM S I I. Circular coded target for automation of optical 3D-measurement and camera calibration [J]. International Journal of Pattern Recognition and Artificial Intelligence, 2001,15(6):905-919.

王忠石徐心和.棋盘格模板角点的自动识别与定位[J].中国图象图形学报, 2007, 12(4):618-622.

WANG Zhongshi,XU Xinhe. Auto-recognition and auto-location of the checkerboard pattern corners [J]. Journal of Image and Graphics, 2007,12(4):618-622.

倪争技张永康.亚像素理论在图像边界处理中的应用研究[J].光学仪器, 2006, 28(3):46-51.

NI Zhengji,ZHANG Yongkang. Application of sub-pixel theory in improving image edge detection [J]. Optical Instruments, 2006, 28(3):46-51.

TSAI R Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses [J]. IEEE Journal of Robotics and Automation, 1987, 3(4):323-344.

HEIKKILA J, SILVEN O. A four-step camera calibration procedure with implicit image correction [C]∥Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Los Alamitos, CA, USA: IEEE Computer Society, 1997: 1106-1112.

ZHANG Zhengyou. Flexible camera calibration by viewing a plane from unknown orientations [C]∥Proceedings of Seventh International Conference on Computer Vision. Piscataway, NJ, USA: IEEE, 1999: 666-673.

STURM P F, MAYBANK S J. On plane-based camera calibration: a general algorithm, singularities, applications [C]∥Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Los Alamitos, CA, USA:IEEE Computer Society, 1999: 432-437.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

超临界二氧化碳向心透平轮背间隙内风阻损失及流动特性研究

多工况下离心压气机叶轮-机匣一体联合设计优化

超临界水异常区域热力学特性研究

离子液体改性燃料的电流体动力学效应研究

语义区分和子图整合驱动的知识图谱表示学习方法