首页 > 论文 > 光学学报 > 37卷 > 9期(pp:915001--1)

一种改进的基于直线特征的非量测畸变校正方法

An Improved Non-Metric Distortion Calibration Method Based on Straight Line Characteristics

  • 摘要
  • 论文信息
  • 参考文献
  • 被引情况
  • PDF全文
分享:

摘要

在大型结构件的损伤监测过程中, 摄像机镜头畸变往往引起成像畸变, 如果直接利用畸变图像进行标定、测量, 将引起较大误差, 降低损伤监测精度。为了有效地校正成像畸变, 提出一种改进的基于直线特征的非量测畸变校正方法。分析实际测量中成像畸变的像差模型; 直接利用场景中存在的直线特征, 得到带权重因子的直线射影不变约束关系和三点近似共线约束关系, 并建立两组畸变校正约束方程求解畸变系数; 通过实验验证提出方法的可行性和有效性。校正结果表明, 相比不带权重的直线特征标定方法, 提出方法优化结果的均方根误差精度提高了0.21 pixel。

Abstract

The camera lens distortion often causes image distortion during damage monitoring process of large structures, great errors will be resulted and damage detection accuracy will be reduced if the distorted image is directly used for calibration and measurement. We propose an improved non-metric distortion calibration method based on straight line characteristics to correct the distortion effectively. Firstly, we analyze the aberration model of the distorted image in actual measurement. Then, we obtain the constraint relationships with weighting factors based on the principle of linear projective invariance and three-point approximate collinearity according to the straight line features in the scene, and establish two sets of distortion correction constraint equations to solve the distortion parameters. Finally, the feasibility and validity of the proposed method is demonstrated experimentally. Root mean square error of the proposed method is improved by 0.21 pixel compared with the calibration method based on the linear feature without weighting factors.

投稿润色
补充资料

中图分类号:TP391.4

DOI:10.3788/aos201737.0915001

所属栏目:机器视觉

基金项目:国家自然科学基金(61573365,61025014)

收稿日期:2017-04-10

修改稿日期:2017-05-07

网络出版日期:--

作者单位    点击查看

刘炼雄:火箭军工程大学控制工程系, 陕西 西安 710025
胡昌华:火箭军工程大学控制工程系, 陕西 西安 710025
何 川:火箭军工程大学核工程系, 陕西 西安 710025
周志杰:火箭军工程大学控制工程系, 陕西 西安 710025
赵玉山:火箭军工程大学控制工程系, 陕西 西安 710025

联系人作者:刘炼雄(liu_lxly@163.com)

备注:刘炼雄(1993-), 男, 硕士研究生, 主要从事无损检测及计算机视觉方面的研究。

【1】Yu Qifeng, Shang Yang. Videometrics: Principles and researches[M]. Beijing: Science Press, 2009: 53-55.
于起峰, 尚 洋. 摄像测量学原理与应用研究[M]. 北京: 科学出版社, 2009: 53-55.

【2】Yang Biwu, Guo Xiaosong. Overview of nonlinear distortion correction of camera lens[J]. Journal of Image and Graphics, 2005, 10(3): 269-273.
杨必武, 郭晓松. 摄像机镜头非线性畸变校正方法综述[J]. 中国图象图形学报, 2005, 10(3): 269-273.

【3】Huang Yingqing, Wen Jun, Xie Zhihong. Research on non-metric calibration algorithm of camera lens distortion[J]. Modern Electronics Technique, 2015, 38(20): 59-62.
黄应清, 文 军, 谢志宏. 摄像机畸变的非量测校正方法研究[J]. 现代电子技术, 2015, 38(20): 59-62.

【4】Herráez J, Denia J L, Navarro P, et al. Determining image distortion and PBS (point of best symmetry) in digital image using straight line matrices[J]. Measurement, 2016, 91: 641-650.

【5】Zhai You, Zeng Luan, Xiong Wei. A simple calibration method for image center and aspect ratio[J]. Optical Technique, 2015, 41(5): 390-394.
翟 优, 曾 峦, 熊 伟. 图像中心和纵横比的简易标定方法[J]. 光学技术, 2015, 41(5): 390-394.

【6】Zhang Min, Jin Longxu, Li Guoning, et al. Camera distortion calibration method based on straight line characteristics[J]. Acta Optica Sinica, 2015, 35(6): 0615001.
张 敏, 金龙旭, 李

【7】Zhou Ziqing, Zhao Peng, Li Bo, et al. Nonmetric lens distortion calibration based on collinear vectors[J]. Acta Optica Sinica, 2014, 34(10): 1015001.
周子卿, 赵 鹏, 李 勃, 等. 基于共线向量的非量测镜头畸变校正[J]. 光学学报, 2014, 34(10): 1015001.

【8】Liu Yang, Liu Wei, Xu Pengtao, et al. Calibration of lens distortion parameters based on two view geometry of translation motion[J]. Optics and Precision Engineering, 2016, 24(4): 922-928.
刘 阳, 刘 巍, 徐鹏涛, 等. 基于纯平移两视图几何的镜头畸变参数标定[J]. 光学 精密工程, 2016, 24(4): 922-928.

【9】Madsen K, Nielsen H B, Tingleff O. Methods for non-linear least squares problems[M]∥Informatics and mathematical modelling. Lyngby: Technical University of Denmark Press, 2004: 17-45.

【10】Malis E, Cipolla R. Multi-view constraints between collineations: Application to self-calibration from unknown planar structures[C]. 6th European Conference on Computer Vision, 2000, 1843: 610-624.

【11】Sun Q, Wang X Y, Xu J P, et al. Camera self-calibration with lens distortion[J]. Optik-International Journal for Light and Electron Optics, 2016, 127(10): 4506-4513.

【12】Brown D C. Close-range camera calibration[J]. Photogrammetric Engineering and Remote Sensing, 1971, 37(8): 855-866.

【13】Jiang Dazhi, Yu Qian, Wang Bingyang, et al. Research and overview of imaging nonlinear distortion in computer vision[J]. Computer Engineering, 2001, 27(12): 108-110.
姜大志, 郁 倩, 王冰洋, 等. 计算机视觉成象的非线性畸变研究与综述[J]. 计算机工程, 2001, 27(12): 108-110.

【14】Weng J Y, Cohen P, Herniou M. Camera calibration with distortion models and accuracy evaluation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(10): 965-970.

【15】Qu Xuejun, Zhang Lu. Camera calibration technique for computer vision detection[J]. Computer Engineering and Design, 2010, 31(19): 4321-4323.
曲学军, 张 璐. 基于空间平行直线束的CCD摄像机内外参数标定[J]. 计算机工程与设计, 2010, 31(19): 4321-4323.

【16】Zhang Jing, Zhu Dayong, Jia Xiaodong. Camera lens distortion calibration with co-line points[J]. Laser Technology, 2006, 30(2): 221-224.
张 靖, 朱大勇, 贾晓东. 用共线点列标定摄像机镜头畸变[J]. 激光技术, 2006, 30(2): 221-224.

【17】邾继贵, 罗 明, 陶国志, 等. 摄像机镜头径向畸变中心的计算模型及求解[J]. 仪器仪表学报, 1998, 19(1): 84-86, 90.

【18】Wang Guiping, Wang Huifeng, Liu Panzhi, et al. A distortion field-calibrating method based on feature parallel lines of image[J]. Acta Photonica Sinica, 2014, 43(1): 0111001.
汪贵平, 王会峰, 刘盼芝, 等. 特征平行直线的成像畸变现场校正[J]. 光子学报, 2014, 43(1): 0111001.

【19】Zhu H J, Wang X, Zhou J L, et al. Approximate model of fisheye camera based on the optical refraction[J]. Multimedia Tools and Applications, 2014, 73(3): 1445-1457.

【20】Zheng Yi, Liu Shangqian. Line-based nonlinear distortion correction of a calibration image[J]. Chinese Journal of Scientific Instrument, 2007, 28(6): 1129-1133.
郑 毅, 刘上乾. 利用直线特征的定标图像非线性畸变校正[J]. 仪器仪表学报, 2007, 28(6): 1129-1133.

引用该论文

Liu Lianxiong,Hu Changhua,He Chuan,Zhou Zhijie,Zhao Yushan. An Improved Non-Metric Distortion Calibration Method Based on Straight Line Characteristics[J]. Acta Optica Sinica, 2017, 37(9): 0915001

刘炼雄,胡昌华,何 川,周志杰,赵玉山. 一种改进的基于直线特征的非量测畸变校正方法[J]. 光学学报, 2017, 37(9): 0915001

您的浏览器不支持PDF插件,请使用最新的(Chrome/Fire Fox等)浏览器.或者您还可以点击此处下载该论文PDF