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A Comprehensive Review of 3D Laser Scanning Point Cloud Data Processing Techniques: Assessing the Dominant Focus and Exploring 3D Modeling and Data Optimization


Article Information

Title: A Comprehensive Review of 3D Laser Scanning Point Cloud Data Processing Techniques: Assessing the Dominant Focus and Exploring 3D Modeling and Data Optimization

Authors: Ke Duan, Jasmin D Niguidula, Bang Hou

Journal: International Journal of Membrane Science and Technology

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30

Publisher: Cosmos Scholars Publishing House

Country: Pakistan

Year: 2023

Volume: 10

Issue: 1

Language: English

Keywords: 3D Laser ScanningPoint Cloud DenoisingPoint Cloud Data Processing.

Categories

Abstract

Three-dimensional laser scanning technology primarily relies on dense scanning points to collect vectorized information of the target object and perform point cloud data processing without physical contact. There are numerous case studies in various fields regarding the use of three-dimensional laser scanning technology for point cloud data acquisition of different objects. By utilizing a three-dimensional laser scanner, precise three-dimensional data of the object's surface can be obtained, effectively meeting the high-precision measurement requirements of three-dimensional points on the object. The main objective of this study is to determine the most suitable point cloud processing method for preprocessing the solid obtained through laser-based 3D scanning. To achieve this goal, we systematically reviewed and reported the technical papers discussing/proposing point cloud data acquisition and processing techniques based on 3D laser scanning technology. As a result of our search, we collected 31 papers on this topic. In this report, we present the process of data collection, result analysis, and classification of related studies. The classification is based on the applicability of methods in processing point cloud data using 3D laser scanning technology. The proposed research clearly demonstrates the latest approaches in data processing in this field and highlights areas that remain unexplored, providing potential avenues for further research.


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