A COMPARISON STUDY BETWEEN B-SPLINE SURFACE FITTING AND RADIAL BASIS FUNCTION SURFACE FITTING ON SCATTERED POINTS
DOI:
https://doi.org/10.11113/jt.v78.9007Keywords:
3D scattered data, approximation, bicubic B-spline surface, radial basis function, noisy dataAbstract
This paper looks in the effectiveness of bicubic B-spline surface fitting and radial basis function, specifically the thin plate spline surface fitting in constructing the surface from the set of scattered data three dimensions (3D) points. Modification of the B-spline approximation algorithm is used to determine the unknown B-spline control points, followed by the construction of the bicubic B-spline surface patch, which can be joined together to form the final surface. The non-interpolation scheme of thin plate spline is also used to fit the data points in this study. The sample of scattered data points is chosen from a specific region in the point set model by using k-nearest neighbour search method. Observation is further carried out to observe the effect of noise in the bicubic B-spline surface fitting and the thin plate spline surface fitting. From the visual aspect, non-interpolation scheme of thin plate spline fits the surface better than bicubic B-spline in the presence of noises. Â
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