Abstract
The measurement of shaft’s size by computer is the significant basis of the automatic industrial measurement and detection, this paper establishes the optoelectronic imaging instrument of the shaft, and the image data of shaft neck is acquired by the industrial camera. In the part of the image pre-processing, we propose the enhancement algorithm of edge line based on the binarization of the gradient operator to enhance the image’s edge line. After the selection of the edge lines by the user in the local region, the paper proposes a measurement method based on the paralleled edge line’s fitting and computing, which can measure the diameter of the shaft neck with the accuracy of sub-pixel. This method contains some key techniques such as the modification of the local region chosen by the user, the selection of the sample points, the fitting of the edge line, the computing method of the diameter size and so on. With the comparison of the conventional line detecting algorithm such as Hough transformation, this proposed algorithm can improve the measurement accuracy of the geometry size. In the part of the experimental results’ exhibition, we use the proposed algorithm to measure another shaft neck’s parameter and verify that the algorithm has the robust characteristic, with the comparison of the optoelectronic measurement result and the artificial measurement result, the reliability of the algorithm is verified.
This work is supported by Innovation Driven Development Special Fund Project of Guangxi (No. AA18118002-3), Guangxi Provincial Natural Science Foundation of China (No. 2020GXNSFBA297077, No. 2018GXNSFAA294065), Key Laboratory Co-sponsored Foundation by Province and Ministry (No. CRKL200103) and the Project of Foundational Research Ability’s Improvement for Young and Middle-aged Teachers of University in Guangxi (No. 2020KY05019).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Costa, P.B., Leta, F.R., de Oliveira Baldner, F.: Computer vision measurement system for standards calibration in XY plane with sub-micrometer accuracy. Int. J. Adv. Manuf. Technol. 105(1–4), 1531–1537 (2019). https://doi.org/10.1007/s00170-019-04297-7
Liu, Y., Liu, J., Ke, Y.: A detection and recognition system of pointer meters in substations based on computer vision. Measurement 152, 107333 (2020)
Liu, Y., Li, G., Zhou, H., Xie, Z., Feng, F., Ge, W.: On-machine measurement method for the geometric error of shafts with a large ratio of length to diameter. Measurement 176, 109194 (2021). https://doi.org/10.1016/j.measurement.2021.109194
Fan, J.F., Jing, F.S.: Dimensional inspecting system of shaft parts based on machine vision. In: 2017 Chinese Automation Congress, pp. 1708–1714. IEEE (2017)
Wang, H.C., et al.: Gradient adaptive image restoration and enhancement. In: International Conference on Image Processing, pp. 2893–2896. IEEE (2006)
Ding, C., Dong, L.L., Xu, W.H.: A fast algorithm based on image gradient field reconstructing. In: International Conference on Digital Image Processing, 100333C. SPIE (2016)
Zhou, C.D., et al.: Partial differential equation based image edge enhancement. In: 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 972–978. IEEE (2016)
Ding, C., Dong, L.L., Xu, W.H.: Image gradient histogram’s fitting and calculation. J. Eng. 2018(1), 45–48 (2018). https://doi.org/10.1049/joe.2017.0406
Saini, S., Sardana, H., Pattnaik, S.: GUI for coordinate measurement of an image for the estimation of geometric distortion of an opto-electronic display system. J. Instit. Eng. (India) B 98(3), 303–310 (2016). https://doi.org/10.1007/s40031-016-0266-0
Ge, J., et al: Multi-scale shaft part’s image edge detection and measurement based on wavelet transform. In: 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, no. 1, pp. 371–375 (2008)
Deeptaroop, M., Rajan, Niharika, S.: Seismic data interpretation using Hough transformation technique. In: 2015 1st International Conference on Next Generation Computing Technologies (NGCT), pp. 580–583 (2015)
Szilvia, N., et al.: Fuzzy Hough transformation in aiding computer tomography based liver diagnosis. In: 2019 IEEE AFRICON. IEEE (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Ding, C., Gao, X., Li, J., Hu, Z., Zhang, W., Wu, Z. (2021). The Computer Measurement Method Research on Shaft’s Size by the Platform of the Optoelectronic Imaging. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12888. Springer, Cham. https://doi.org/10.1007/978-3-030-87355-4_47
Download citation
DOI: https://doi.org/10.1007/978-3-030-87355-4_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-87354-7
Online ISBN: 978-3-030-87355-4
eBook Packages: Computer ScienceComputer Science (R0)