Document Type : Research Paper

Authors

1 Production Engineering and Metallurgy Dept. University of Technology - Iraq

2 Production Engineering and Metallurgy Dept. University of Technology Baghdad - Iraq

Abstract

3D laser scanner is one of the modern technologies, which used to obtain the geometric information about the 3D scanned object surface. But, there are some problems that are associated with this technique such as the huge number of obtained points which require high memory to save and the required data processing processes. This paper proposed a data simplification algorithm for point cloud of a scanned object using 3D laser scanner (Matter
and Form) in a manner to extract the necessary geometric features, which are
represented by points for a 3D object. This algorithm based on the
instantaneous calculation of chord height of each set of adjacent points in the
point cloud. A MATLAB environment was used to build a proposed
simplification algorithm program. Then this program was applied using a
proposed case study. The result which was obtained from the application of the
proposed algorithm and surface fitting process for the proposed case study
proved the effectiveness of the proposed algorithm in data simplification. The
percent of data which was ignored as noisy data point was (24%) of the total
number of data point in applying the algorithm for two attempts.
3D laser scanner is one of the modern
technologies, which
used to
obtain the geometric information about the 3D scanned object surface.
But,
there are some
problems
that
are
associated with this technique such as the
huge number of obtained points
which
require high memory to save
and
the
required data processing processes.
Th
is paper proposed a data simplification
algorithm for point cloud of a
scanned obje
ct using 3D laser scanner (Matter
and Form) in a
manner to extract the necessary geometric features, which
are
represented by points for a 3D object. This algorithm based on
the
instantaneous calculation of chord height of each set of adjacent points in th
e
point cloud. A MATLAB environment was
used to build a proposed
simplification algorithm program
. Then
this program
was
appli
ed using a
proposed case study.
The result which was obtained from
the
application
of
the
proposed algorithm and surface fitting process for the proposed case study
proved the effectiveness of the proposed algorithm in data simplification.
The
percent of data which was ignored as noisy data point was (24%)
of the
total
number of data point in applying the algorithm for two attempts.

Keywords

Main Subjects

[1] G. Wang, Y. Lv, N. Han, and D. Zhang, ’’Simplification Method and Application of 3D Laser Scan Point Cloud Data’’, International Conference on Mechanical Engineering and Material Science, MEMS, 2012. [2] J. Liu, J. Zhao, X. Yang, J. Liu, X. Qu, and X. Wang, “A Reconstruction Algorithm for Blade Surface Based on Less Measured Points”, Hindawi Publishing Corporation, IJAE, International Journal of Aerospace Engineering, Vol. 2015, Article ID 431824, 2015. [3] B. Cyganek, B. Krawczyk, and M. Woźniak, ”Multidimensional Data Classification with Chordal Distance Based Kernel and Support Vector Machines”, Elsevier, EAAI, Engineering Applications of Artificial Intelligence, Vol. 46 pp. 10–22, 2015. [4] M. Xiao, Z. Qi, and H. Shi, “The Surface Flattening based on Mechanics Revision of the Tunnel 3D Point Cloud Data from Laser Scanner”, Elsevier, Procedia Computer Science, Vol. 131, pp. 1229– 1237, 2018. [5] Z. Kang, L. Zhang , L. Tuo, B. Wang, and J. Chen, “Continuous Extraction of Subway Tunnel Cross Sections Based on Terrestrial Point Clouds “, Remote Sensing journal, Vol. 2072-4292, pp. 857-879, 2014 . [6] J. Kisztnera, J. Jelíneka, T. Daneka, and J. Ruzicka, “3D Documentation of Outcrop by Laser Scanner — Filtration of Vegetation“, Elsevier, Journal of Perspectives in Science, Vol. 7, pp. 161—165, 2016. [7] S. Gauthier, W. Puech, R. Bénière, and G. Subsol, “Analysis of Digitized 3D Mesh Curvature Histograms for Reverse Engineering”, Elsevier, Computers in Industry, Vol. 82, pp. 67–83, 2017. [8] C. Mineo, S. G. Pierce, and R. Summan, ’’ Novel Algorithms for 3D Surface Point Cloud Boundary Detection and Edge Reconstruction’’, CDE, journal of Computational Design and Engineering, Vol. 6, pp. 81–91, 2019. [9] K. W. Lee, and P. Bo, “Feature Curve Extraction from Point Clouds via Developable Strip Intersection”, Elsevier, journal of Computational Design and Engineering, Vol. 3, pp. 102–111, 2016. [10] Peter Comninos, “Mathematical and Computer Programming Techniques for Computer Graphics”, Springer, Verlag, London, 2006.