Point Cloud Pre-Processing and Surface Reconstruction Based on Chord Algorithm Technique | ||
Engineering and Technology Journal | ||
Article 3, Volume 37, 9A, September 2019, Pages 364-368 PDF (268.29 K) | ||
Document Type: Research Paper | ||
DOI: 10.30684/etj.37.9A.3 | ||
Authors | ||
Ali M. Al-Badairy1; Ahmed A. Al-Duroobi2; Maan A. Tawfiq1 | ||
1Production Engineering and Metallurgy Dept. University of Technology - Iraq | ||
2Production 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 | ||
Chord Algorithm; Point Cloud; Surface Reconstruction | ||
References | ||
[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. | ||
Statistics Article View: 228 PDF Download: 204 |