Abstract
This paper presents a novel method for estimating the degree of deformations in 3D prints. The increased popularity of three-dimensional printing techniques introduces a necessity to create methods for quality assessment of printed materials. One of the key problems of 3D printing are strains and deformations of printed objects. This problem is determined by many factors like: printing material (filament), object geometry or temperature. The conducted research is focused on a method of automatic analysis of deformations in 3D prints based on surface scans of objects. In our research some surface scans containing varying degrees of deformations have been used for verification of obtained results. In order to evaluate the degree of deformations of materials a local cross-correlation with Monte Carlo sampling have been used. Tests carried on multiple samples have shown that the local cross-correlation technique works well when assessing the degree of deformations of printed objects on the basis of surface scans. The obtained results show that our method can be further applied for improvement of the quality of the objects received from 3D printers.
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Fastowicz, J., Bąk, D., Mazurek, P., Okarma, K. (2018). Estimation of Geometrical Deformations of 3D Prints Using Local Cross-Correlation and Monte Carlo Sampling. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications Challenges 9. IP&C 2017. Advances in Intelligent Systems and Computing, vol 681. Springer, Cham. https://doi.org/10.1007/978-3-319-68720-9_9
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DOI: https://doi.org/10.1007/978-3-319-68720-9_9
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