Development of a method for improving the accuracy of measurement of linear measures of 3D models via scanning

Authors

DOI:

https://doi.org/10.15587/2706-5448.2021.243983

Keywords:

3D scanning, subjective error, instrumental error, linear dimensions, image projection, photogrammetry

Abstract

The object of research is to refine the linear sizes of the obtained 3D models via scanning, and reducing the numbers of errors when obtaining the model. For now, there is no accuracy method for transferring the actual sizes of an object to a 3D model. One of the most problematic places in the existing methods of transferring sizes from the object to the model is the error in the placement of dimensional markers due to inaccuracy, or poor quality of the received surface via scanning.

A model of the instrument complex is used to implement an improved method of 3D scanning, based on the photogrammetric method. The advanced technology of construction and measurement of 3D models on the basis of photos on the principle of stereo pairs in combination with image projection is based on a combination of existing scanning methods. As well as the introduction of new functionalities, such as maintaining the actual sizes of an object, its textures, color and light characteristics, as well as improving the accuracy of linear sizes.

As a result of the use of a standard, reference projections, and a new method of comparing photographs to build a 3D model, a 60 % increase in the accuracy of linear dimensions was achieved. This is due to the fact that the proposed new combined method incorporates all the existing most important aspects of scanning. And also has a number of features, such as the definition of boundary surfaces, automatic sizing, detection, and processing of glass and mirror surfaces. Due to this, this method eliminates the main disadvantages of the usual photogrammetric method – inaccuracies in the surface quality of the models, and inaccuracies in the transfer of linear dimensions. It is estimated that the combined method will allow to transfer the real size of simple objects in 3D with an accuracy of 99.97 % of the actual size of the object. It will also improve the quality of complex surfaces (boundary, glass, mirror) by at least 40–60 %, compared to other existing methods.

Author Biographies

Volodymyr Kvasnikov, National Aviation University

Doctor of Technical Sciences, Professor, Head of Department

Department of Computerized Electrotechnical Systems and Technologies

Dmytro Ornatskyi, National Aviation University

Doctor of Technical Sciences, Professor

Department of Computerized Electrotechnical Systems and Technologies

Valerii Dostavalov, National Aviation University

Postgraduate Student

Department of Computerized Electrotechnical Systems and Technologies

References

  1. Várady, T., Martin, R. R., Cox, J. (1997). Reverse engineering of geometric models – an introduction. Computer-Aided Design, 29 (4), 255–268. doi: http://doi.org/10.1016/s0010-4485(96)00054-1
  2. Je, C., Lee, S. W., Park, R.-H. (2004). High-Contrast Color-Stripe Pattern for Rapid Structured-Light Range Imaging. Computer Vision – ECCV 2004, LNCS 3021. Berlin Heidelberg: Springer-Verlag, 95–107. doi: http://doi.org/10.1007/978-3-540-24670-1_8
  3. Lkeuchi, K. (2001). Modeling from Reality. 3rd International Conference on 3-D Digital Imaging and Modeling. Los Alamitos: IEEE Computer Society, 117–124.
  4. Niezrecki, C., Baqersad, J. (Eds.) (2018). Structural Health Monitoring, Photogrammetry & DIC. Vol. 6: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 210–213. doi: http://doi.org/10.1007/978-3-319-74476-6
  5. Wolf, P. R. (2013). Elements of photogrammetry with application in gis. McGraw-Hill Education, 696.
  6. Gonsales, R., Vuds, R. (2012). Tsifrovaya obrabotka izobrazhenii. Moscow: Tekhnosfera, 1104.
  7. Alpatov, B. A., Babayan, P. V., Balashov, O. E., Stepashkin, A. I. (2008). Metody avtomaticheskogo obnaruzheniya i soprovozhdeniya obektov. Obrabotka izobrazhenii i upravlenie. Moscow: Radiotekhnika, 176.
  8. Mikhailov, A. P., Chibunichev, A. G. (2014). Kurs lektsii po fotogrammetrii. MIIGAiK, 49–54.
  9. Lemmens, M. (2021). An Introduction to Pointcloudmetry: Point Clouds from Laser Scanning and Photogrammetry. Whittles Publishing, 352.
  10. Babak, V. P. (1994). Obrobka syhnaliv pry formuvanni zobrazhen obiektiv. Kyiv: Lybid, 192.
  11. McGlone, J. C., Mikhail, E. M., Bethel, J. S., Mullen, R. (2004). Manual of Photogrammetry. Hardcover, 1151.
  12. Guk, P. D., Bychenok, V. A., Prudnikov, V. V. (2008). Fototopografiya. Novosibirsk, 79.
  13. Nazarov, A. S. (2006). Fotogrammetriya. Minsk: TetraSistems, 368.
  14. Murray, S.; Flynn, R. R. (Ed.) (2002). Graphic Devices. Computer Sciences, Vol 2: Software and Hardware. Macmillan Reference USA, 81–83.

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Published

2021-12-07

How to Cite

Kvasnikov, V., Ornatskyi, D., & Dostavalov, V. (2021). Development of a method for improving the accuracy of measurement of linear measures of 3D models via scanning. Technology Audit and Production Reserves, 6(2(62), 30–36. https://doi.org/10.15587/2706-5448.2021.243983

Issue

Section

Systems and Control Processes: Reports on Research Projects