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Academic Journal of Computing & Information Science, 2020, 3(4); doi: 10.25236/AJCIS.2020.030403.

Complex parts measurement system based on 3D depth vision


Rui Hou*, Hang Zhou

Corresponding Author:
Rui Hou

College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, China
*Corresponding author


with the continuous promotion of the industrial upgrading of the manufacturing industry, the inspection efficiency requirements of the manufacturing industry for parts are becoming higher and higher. At present, the traditional measurement methods include gauge, caliper, profilometer, universal tool microscope, ray and other methods, but with the rapid development of industry, the traditional measurement methods can’t meet the needs of efficient measurement of industrial production line. Vision based measurement technology has the advantages of non-contact, high precision and easy to realize automation. The monocular vision measurement system is simple in structure and easy to operate, and has gradually become an important measurement method in the field of high-precision measurement [1] of part size. But for the detection of complex parts, the conventional 2D vision image is to extract the features of the measured object from the gray image and measure it in the X-Y plane. The method based on the standard scale is difficult to accurately measure the size. Aiming at the problems faced in the current complex parts detection, through the research of image theory, camera calibration theory and visual dimension measurement technology, a 3D depth vision [2] measurement system for complex part size is designed, which combines depth information with 2D vision measurement technology. The experimental results show that the system can meet the requirements of stability, reliability, high precision and strong anti-interference ability in measuring the size of complex parts.


3D depth vision, complex parts, dimension measurement system

Cite This Paper

Rui Hou, Hang Zhou. Complex parts measurement system based on 3D depth vision. Academic Journal of Computing & Information Science (2020), Vol. 3, Issue 4: 21-30. https://doi.org/10.25236/AJCIS.2020.030403.


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