Developing a Rapid Curvature Based Data Reduction Algorithm

  Mohamed Hanafy,  Ahmed Abdelhafiz,  Youssef abbbas

Nowadays, there is a big demand to create 3D digital models for historical places. Huge point clouds have to be reduced wisely to enable meshes generation. Reduction algorithms are used to achieve point clouds with reasonable number of points correctly covers all sites features. The meaning here of the correct points coverage is to be dense at curved regions and distant at plane ones. The state-of-the–art curvature algorithm is time consuming. In this work, a new Rapid Curvature based Data Reduction (RCDR) algorithm is developed to reduce large point clouds rapidly and accurately. The comparison between the developed algorithm and the curvature algorithm shows a 5% reduction in accuracy and a huge amount of time saving in the RCDR algorithm. The point cloud, that takes about 36 hours processing time using the curvature algorithm, takes about 11 minutes using the developed one. So, one can fairly see the efficiency of the developed algorithm.

Keywords- Point Cloud, Data Acquisition, Data Reduction, K-nearest points, Curvature

Unique Identification Number - IJEDR1904095
Page Number(s) - 529-537
Pubished in - Volume 7 | Issue 4 | December 2019
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Mohamed Hanafy,  Ahmed Abdelhafiz,  Youssef abbbas,   "Developing a Rapid Curvature Based Data Reduction Algorithm", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.7, Issue 4, pp.529-537, December 2019, Available at :http://www.ijedr.org/papers/IJEDR1904095.pdf