1. Point Cloud Pre-Processing and Surface Reconstruction Based on 3D Gaussian Curvature Algorithm Technique.
- Author
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Al-Bdairy, Ali M., Al-Duroobi, Ahmed A. A., and Tawfiq, Maan A.
- Subjects
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OPTICAL scanners , *POINT cloud , *GAUSSIAN curvature , *SURFACE reconstruction , *ALGORITHMS , *POINT set theory - Abstract
In recent years, a 3D laser scanner has increasing attention as one of the modern technologies to digitizing the 3D object surface in manner to obtain a mathematical representation of object’s and surface reconstruction. Due to limitations of a 3D laser scanners, the row point cloud, which are acquired from these techniques, included some undesired information such as noise points and associated huge number of points in point cloud. In the present paper, a new proposed point cloud simplification algorithm for scanned object using 3D laser scanner (Matter and Form) has been adopted in manner to extract the necessary geometric features which represented by a 3D surface curvature. This algorithm based on instantaneous calculation of 3D Gaussian curvature for each data point. The curvature value indicates both quality of the topical calculations and a noise isolating and detection in the point cloud set. A MATLAB environment has been adopted to construct a proposed point cloud simplification algorithm program, this program has been proved using a practically case studies. The results proved the effectiveness of the proposed algorithm in local calculation of 3D curvature and detection and isolate the noise points in point cloud where the percent of data which was ignored as noisy data point were (49.29%) and (57.30%), of total data point number after applying the algorithm for the first and second proposed case studies respectively. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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