Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction
Mineo, Carmelo and Pierce, Stephen Gareth and Summan, Rahul (2019) Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction. Journal of Computational Design and Engineering, 6 (1). pp. 81-91. ISSN 2288-4300 (https://doi.org/10.1016/j.jcde.2018.02.001)
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Abstract
Tessellated surfaces generated from point clouds typically show inaccurate and jagged boundaries. This can lead to tolerance errors and problems such as machine judder if the model is used for ongoing manufacturing applications. This paper introduces a novel boundary point detection algorithm and spatial FFT-based filtering approach, which together allow for direct generation of low noise tessellated surfaces from point cloud data, which are not based on pre-defined threshold values. Existing detection techniques are optimized to detect points belonging to sharp edges and creases. The new algorithm is targeted at the detection of boundary points and it is able to do this better than the existing methods. The FFT-based edge reconstruction eliminates the problem of defining a specific polynomial function order for optimum polynomial curve fitting. The algorithms were tested to analyse the results and measure the execution time for point clouds generated from laser scanned measurements on a turbofan engine turbine blade with varying numbers of member points. The reconstructed edges fit the boundary points with an improvement factor of 4.7 over a standard polynomial fitting approach. Furthermore, through adding artificial noise it has been demonstrated that the detection algorithm is very robust for out-of-plane noise lower than 25% of the cloud resolution and it can produce satisfactory results when the noise is lower than 75%.
ORCID iDs
Mineo, Carmelo ORCID: https://orcid.org/0000-0002-5086-366X, Pierce, Stephen Gareth ORCID: https://orcid.org/0000-0003-0312-8766 and Summan, Rahul ORCID: https://orcid.org/0000-0002-4090-4528;-
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Item type: Article ID code: 63217 Dates: DateEvent31 January 2019Published7 February 2018Published Online6 February 2018Accepted20 October 2017SubmittedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 07 Feb 2018 12:44 Last modified: 06 Nov 2024 01:44 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/63217