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  1. Home
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  5. Performance evaluation of different devices and algorithms for modelling small artefact
 
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Performance evaluation of different devices and algorithms for modelling small artefact

Journal
Journal of Physics: Conference Series
ISSN
1742-6588
1742-6596
Date Issued
2023
Author(s)
H Tazudin
Universiti Malaysia Perlis
Shazmin Aniza Abdul Shukor
Universiti Malaysia Perlis
Jalal Johari
Universiti Geomatika Malaysia
DOI
10.1088/1742-6596/2641/1/012026
Handle (URI)
https://iopscience.iop.org/article/10.1088/1742-6596/2641/1/012026
https://iopscience.iop.org/
https://hdl.handle.net/20.500.14170/15364
Abstract
3D reconstruction and modelling play important roles in various applications, specifically in heritage preservation. With the aid of suitable hardware like the 3D sensors as well as respective data processing methods, the work has become more feasible in realizing the aim to conserve and preserve more artefacts. However, too many choices and alternatives might lead to different results which may affecting the preservation purpose. The objective of this work is to analyze and evaluate the performance of different devices and algorithms for small artefact modelling. Two 3D sensors, iPhone 13 Pro Max LiDAR and Structure sensor were selected to collect data of small artefact to be reconstructed and modelled. Two main, important surface reconstruction algorithms which are Poisson and Ball-Pivoting methods were also selected to be tested. Specifications of the sensors’ capabilities as well as modelling results of the artefact are examined. Different parameters of the algorithms were selected to study their effect. These findings will help to learn more about 3D sensors and the suitable modelling methods in making them better for usage in a variety of areas, including archaeology, architecture, and the protection of cultural heritage.
Subjects
  • Historic preservation...

  • Image reconstruction

  • Surface reconstructio...

  • Three-dimensional com...

File(s)
Performance Evaluation of Different Devices.pdf (1.51 MB)
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7
Acquisition Date
Jan 12, 2026
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Acquisition Date
Jan 12, 2026
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