首页 > 论文 > 光学学报 > 39卷 > 10期(pp:1015002--1)

无编码点的工业摄影测量技术的研究及实现

Research and Implementation of Industrial Photogrammetry Without Coded Points

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

摘要

工业摄影测量在航空航天、机械制造、零件装配、产品外形检测等方面有着广泛的应用[1]。在利用单相机围绕被测物体进行自由拍摄的过程中,通常需要借助计算机视觉的相关理论知识来完成各次拍摄时相机位姿的求解和目标点三维重建。在构建多视图几何结构[2]的方法上,大部分的工业摄影测量系统都需要事先在被测物表面布设特征明显的标志物(编码点)[3],并需要根据图像上提取出的特征中心点来建立多图的同名匹配点信息。工业零件表面的色泽一般较为单一,缺乏丰富的特征信息。编码点则可以提供易于识别的视觉标志物,且编码点具有规则化的几何图形,便于提取出精确的图像特征点,从而完成高精度的多视图几何结构的求解。然而,在物体表面布设编码点比较耗时、繁琐,尤其当被测物是飞机蒙皮之类的大型复杂的产品零件时,所需的编码点数量可能多达上百个。此外,有些零件表面不允许粘贴标记点或不具备布点条件,例如,非铁磁性的金属材料无法使用磁吸附式的编码标志物,只能依靠粘贴的方式来固定编码点,这可能对高精度的零件表面造成破坏。

Abstract

Placing a certain number of coded points is generally required in the current industrial photogrammetry system. However, many industrial products are not suitable for the arrangement of coded points. This study proposes a novel method of industrial photogrammetry without using coded points. Our method only requires a projection device to project the speckle texture, a scale bar to recover scale, and a multi-angle camera to capture various images of the measured object. A “coarse-to-fine” two-step reconstruction strategy is devised to solve the multi-view geometry with high precision. Moreover, a rotation-free digital image correlation (RFDIC) method is proposed for high-accuracy point-matching between images with large rotational angles. The experimental results verify that the error in measuring the length of scale bar by the RFDIC method is below 0.01 mm/m and the error of the RFDIC method compared with that of the latest commercial point cloud construction method for three dimensional measurement system can reach approximately 0.055 mm, which satisfies the precision requirements of industrial photogrammetry.

Newport宣传-MKS新实验室计划
补充资料

DOI:10.3788/AOS201939.1015002

所属栏目:机器视觉

基金项目:国家自然科学基金、江苏省基础研究计划、上海航天科技创新基金资助项目;

收稿日期:2019-04-10

修改稿日期:2019-06-21

网络出版日期:2019-10-01

作者单位    点击查看

严俊:南京航空航天大学机电学院, 江苏 南京 210016
叶南:南京航空航天大学机电学院, 江苏 南京 210016
李廷成:南京航空航天大学机电学院, 江苏 南京 210016
祝鸿宇:南京航空航天大学机电学院, 江苏 南京 210016

联系人作者:叶南(yen@nuaa.edu.cn)

备注:国家自然科学基金、江苏省基础研究计划、上海航天科技创新基金资助项目;

【1】Huang G P. Digital close range industry photogrammetry. (2016).
黄桂平. 数字近景工业摄影测量理论、方法与应用. (2016).

【2】Hartley R and Zisserman A. Multiple view geometry in computer vision. (2003).

【3】Song L M, Chen C M, Chen Z et al. Detection and recognition of cyclic coded targets. Optics and Precision Engineering. 21(12), 3239-3247(2013).
宋丽梅, 陈昌曼, 陈卓 等. 环状编码标记点的检测与识别. 光学精密工程. 21(12), 3239-3247(2013).

【4】Agarwal S, Furukawa Y, Snavley N et al. Reconstructing Rome. Computer. 43(6), 40-47(2010).

【5】Lowe D G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision. 60(2), 91-110(2004).

【6】Bay H, Ess A, Tuytelaars T et al. Speeded-up robust features (SURF). Computer Vision and Image Understanding. 110(3), 346-359(2008).

【7】Bruck H A. McNeill S R, Sutton M A, et al. Digital image correlation using Newton-Raphson method of partial differential correction. Experimental Mechanics. 29(3), 261-267(1989).

【8】Pan B and Li K. A fast digital image correlation method for deformation measurement. Optics and Lasers in Engineering. 49(7), 841-847(2011).

【9】Pan B, Xie H M and Li Y J. Three-dimensional digital image correlation method for shape and deformation measurement of an object surface. Journal of Experimental Mechanics. 22(6), 556-567(2007).
潘兵, 谢惠民, 李艳杰. 用于物体表面形貌和变形测量的三维数字图像相关方法. 实验力学. 22(6), 556-567(2007).

【10】Harvent J, Coudrin B, Brèthes L et al. Multi-view dense 3D modelling of untextured objects from a moving projector-cameras system. Machine Vision and Applications. 24(8), 1645-1659(2013).

【11】Zhang K W, Liang J, You W et al. Fast morphology measurement based on the binocular vision and speckle projection. Laser & Infrared. 46(12), 1517-1520(2016).
张扣文, 梁晋, 尤威 等. 基于双目视觉和散斑投射的快速形貌测量. 激光与红外. 46(12), 1517-1520(2016).

【12】Hang C and Yan Q. Structural surface topography measurement based on projection speckle method. Science Technology and Engineering. 18(19), 230-236(2018).
杭超, 燕群. 基于投影散斑的结构表面形貌测量. 科学技术与工程. 18(19), 230-236(2018).

【13】Zhong F and Quan C. Digital image correlation in polar coordinate robust to a large rotation. Optics and Lasers in Engineering. 98, 153-158(2017).

【14】LePage W S, Shaw J A and Daly S H. Optimum paint sequence for speckle patterns in digital image correlation. Experimental Techniques. 41(5), 557-563(2017).

【15】Ye N and Zhang L Y. Improved fractionized displacement transfer algorithm based on digital image correlation in large deformation applications. Acta Optica Sinica. 30(4), 976-983(2010).
叶南, 张丽艳. 大变形下基于数字图像相关的改进分段位移传递法. 光学学报. 30(4), 976-983(2010).

【16】Ye N and Zhang L Y. Key techniques and system of sheet metal forming limit strain measurement based on stereo vision. Acta Aeronautica et Astronautica Sinica. 31(10), 2093-2102(2010).
叶南, 张丽艳. 基于立体视觉的板料成形极限应变测量关键技术及其系统. 航空学报. 31(10), 2093-2102(2010).

【17】Furukawa Y and Ponce J. Accurate, dense, and robust multiview stereopsis. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32(8), 1362-1376(2010).

【18】Schonberger J L and Frahm J M. Structure-from-motion revisited. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE. 4104-4113(2016).

【19】Snavely N. Bundler: Structure from Motion (SfM) for Unordered Image Collections [2019-03-22].http: ∥www.cs.cornell.edu/~snavely/bundler/. (0).

【20】Wu C C. VisualSFM: a visual structure from motion system [2019-03-22].http: ∥ccwu.me/vsfm/. (0).

【21】Moulon P, Monasse P, Perrot R et al. OpenMVG: open multiple view geometry. ∥Kerautret B, Colom M, Monasse P. Reproducible research in pattern recognition. Lecture notes in computer science. Cham: Springer. 10214, 60-74(2017).

引用该论文

Jun Yan,Nan Ye,Tingcheng Li,Hongyu Zhu. Research and Implementation of Industrial Photogrammetry Without Coded Points[J]. Acta Optica Sinica, 2019, 39(10): 1015002

严俊,叶南,李廷成,祝鸿宇. 无编码点的工业摄影测量技术的研究及实现[J]. 光学学报, 2019, 39(10): 1015002

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