DOI: https://doi.org/10.18517/ijods.2.2.77-84.2021
Machine Vision and Metrology Systems: An Overview
Abstract
Metrology and machine vision are two fields that have been considered together frequently due to the versatility of artificial vision to solve industrial inspection problems. Metrology is one of the many applications of machine vision, which has the advantage that allows for the inspection of a total production batch that leaves an assembly line without creating a bottleneck in production. The aim of this paper is to present an overview of the current advancement in machine vision and metrology systems. The paper exposes a wide range of machine vision software aimed at the inspection of application processes, systematically highlighting the relationship between machine vision and metrology systems. Some applications of machine vision and metrology for quality control inspections are also highlighted.
Article Details
How to Cite
[1]
D. K. Moru, D. Agholor, and F. A. Imouokhome, “Machine Vision and Metrology Systems: An Overview”, Int. J. Data. Science., vol. 2, no. 2, pp. 77-84, Dec. 2021.
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References
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B. G. Batchelor, Machine Vision Handbook. Springer, 2012.
S. Andonov and M. Cundeva-Blajer, “Calibration for industry 4.0 metrology: touchless calibration,” in Journal of Physics: Conference Series, vol. 1065, p. 072019, IOP Publishing, 2018.
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Q. Hou, J. Sun, and P. Huang, “A novel algorithm for tool wear on- line inspection based on machine vision,” The International Journal of Advanced Manufacturing Technology, vol. 101, no. 9, pp. 2415–2423, 2019.
J. Schlett, “Machine vision helps adhesive trend stick in auto industry,” Photonics Media, 2016.
M. T. Habib, A. Majumder, A. Jakaria, M. Akter, M. S. Uddin, and F. Ahmed, “Machine vision based papaya disease recognition,” Journal of King Saud University-Computer and Information Sciences, vol. 32, no. 3, pp. 300–309, 2020.
D. K. Moru and D. Borro, “Improving optical pipeline through better alignment and calibration process,” The International Journal of Advanced Manufacturing Technology, vol. 114, no. 3, pp. 797–809, 2021.
A. A. Robie, K. M. Seagraves, S. R. Egnor, and K. Branson, “Machine vision methods for analyzing social interactions,” Journal of Experimental Biology, vol. 220, no. 1, pp. 25–34, 2017.
C. Steger, M. Ulrich, and C. Wiedemann, Machine vision algorithms and applications. John Wiley & Sons, 2018.