Open AccessSurface roughness estimation by using a 3D model reconstructed from multiple images
Author(s) -
A. E. Viktorenkov,
P. U. Yakimov
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/5/052037
Subject(s) - point cloud , profilometer , surface finish , photogrammetry , scaling , surface roughness , 3d reconstruction , basis (linear algebra) , 3d model , gaussian filter , gaussian , point (geometry) , filter (signal processing) , plane (geometry) , geometry , computer science , computer vision , mathematics , materials science , artificial intelligence , physics , image (mathematics) , quantum mechanics , composite material
In this paper, the roughness parameters of the part are estimated based on its reconstructed 3D model. Reconstruction of the 3D model was carried out using the structure from motion photogrammetry method. Preliminary processing of the 3D model consisted in fitting the plane to the point cloud of the 3D model using the least squares method, aligning and scaling the 3D model. Also, the resulting 3D model was approximated using the radially basic functions to obtain a uniform cloud of points. Next, the obtained point cloud was filtered to identify 2D and 3D roughness profiles. As filters, a Gaussian filter and 2RC were used. The roughness parameters of the obtained profiles were calculated. A comparison of the roughness parameters calculated on the basis of the 3D model and the roughness parameters calculated by the BV-7669 profilometer was made.