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@InBook{IPC2017_corr,
  pages     = {67--74},
  title     = {Estimation of Geometrical Deformations of {3D} Prints Using Local Cross-Correlation and {M}onte {C}arlo Sampling},
  publisher = {Springer International Publishing},
  year      = {2018},
  author    = {Fastowicz, Jaros{\l}aw and B{\k{a}}k, Dawid and Mazurek, Przemys{\l}aw and Okarma, Krzysztof},
  editor    = {Chora{\'{s}}, Micha{\l} and Chora{\'{s}}, Ryszard S.},
  address   = {Cham},
  isbn      = {978-3-319-68720-9},
  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.},
  booktitle = {Image Processing and Communications Challenges 9: 9th International Conference, IP{\&}C'2017 Bydgoszcz, Poland, September 2017, Proceedings},
  doi       = {10.1007/978-3-319-68720-9_9},
  url       = {https://doi.org/10.1007/978-3-319-68720-9_9},
}

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