Sub-pixel center extraction method of laser stripe center based on hierarchical processing

被引：0
|
作者：
Liu W. [1 ]
Zhang Y. [1 ]
Gao P. [1 ]
Yang F. [1 ]
Lan Z. [1 ]
Li X. [1 ]
Jia Z. [1 ]
Gao H. [1 ]
机构：
[1] School of Mechanical Engineering, Dalian University of Technology, Dalian
来源：
| 2017年 / Chinese Society of Astronautics卷 / 46期
关键词：
Computer vision; Hierarchical processing; Large parts; Laser stripe extraction; Sub-pixel;
D O I：
10.3788/IRLA201746.1017010
中图分类号：
学科分类号：
摘要：
A sub-pixel center extraction algorithm based on hierarchical processing was proposed for the implementation of laser stripe processing in the large aerospace parts measurement with high speed and precision. Firstly, the high-resolution image was compressed into low-resolution image with structural invariance. Then, the normal vector of the center of laser stripe was calculated by using quadratic curve fitting in the low-resolution image. The normal vector in the low-resolution image was reproduced to the high-resolution image based on the theory of normal regression. The judgment of gray center on normal direction was established to determine calculated pixels. The sub-pixel center of calculated pixels on the normal direction was accurately calculated by the gray weighted centroid method. Finally, the presented method was utilized to measure a composite material standard part and complex aviation parts in the laboratory and assembly testing machine, respectively. Experimental results show that the precision of the reconstruction of a single stripe on the surface of object is 0.269 mm and the precision of three-dimension surface measurement is 0.268 mm. It indicates that the proposed method can improve the speed and precision of the engineering measurement of large part. Moreover, the method can satisfy the requirements of the in-site measurement of large aerial parts. © 2017, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.
引用
收藏
相关论文
共 14 条
  • [1] Zhao S., Lu Y., Chen X., Et al., Realization of real-time automatic target reporting system for simulant airborneweapon attacking over ground, Infrared and Laser Engineering, 43, pp. 78-82, (2014)
  • [2] Li H., Zhang L.X., Xiao T.Y., Real-time control for CPS of digital airplane assembly with robust H -infinity theory, Tsinghua Science and Technology, 20, 4, pp. 376-384, (2015)
  • [3] Gao Y., An Z., Wang J., Et al., Precision measurement technology of 3D surfaces, Infrared and Laser Engineering, 40, 11, pp. 2261-2264, (2011)
  • [4] Shi J., Qian Q., Pang L., Et al., Three- dimensional measurement and registration for large scale plates, Optics and Precision Engineering, 22, 5, pp. 1165-1170, (2014)
  • [5] Zheng X., Wei Z., Zhang G., Expeditions calibration algorithm of visual tracking and measurement system with field coordinate system for moving target, Infrared and Laser Engineering, 44, 7, pp. 2175-2181, (2015)
  • [6] Kieu H., Pan T., Wang Z., Et al., Accurate 3D shape measurement of multiple separate objects with stereo vision, Measurement Science and Technology, 25, 1, pp. 35-40, (2014)
  • [7] Qu H., Zhang Q., Ruan Y., Laser radar based on scanning image tracking, Chinese Optics, 5, 3, pp. 242-247, (2012)
  • [8] Feng P., Liu Z., Automatic localization method of the multi-planar strip in rudder angle measurement, Chinese Optics, 7, 6, pp. 911-916, (2014)
  • [9] Lukas J., Fridrich J., Goljan M., Detecting digital image forgeries using sensor pattern noise, International Society for Optics and Photonics, (2006)
  • [10] Steger C., An unbiased detector of curvilinear structures, IEEE Pattern Analysis and Machine Intelligence, 20, 2, pp. 113-125, (1998)
12