Parameterization of Unorganized Point Cloud Data for B-Spline Surface Fitting
Vandana Agrawal

Vandana Agrawal, Assistant Professor, Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad (U.P), India
Manuscript received on 05 February 2019 | Revised Manuscript received on 13 February 2019 | Manuscript published on 28 February 2019 | PP: 135-140 | Volume-8 Issue-4, February 2019 | Retrieval Number: D2664028419/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In the present work an algorithm is presented for the parameterization of unorganized point cloud data such that a smooth B-spline surface can be fitted. Points belonging to various surfaces and edges are identified during segmentation. Further edges bounding to segmented region are represented by curves. In the present work initially B-spline curves are constructed with C1 smoothness by interpolating the measured points lying on the edges. For each segmented region four such curves named as boundary curves are constructed to enclose it. Using these boundary curves Coons surface is constructed which serves as base surface for each segmented region. Each Coons surface is divided into grids and for each measured point the nearest grid vertex is found out. The parameters of this vertex are used as the parameters of the measured point. Finally, an algorithm using an iterative approach is given to further improve the parameterization.
Keyword: Parameter, Data Points, Curve, Surfac.
Scope of the Article: Cloud Computing