Robust Detection of Non-overlapping Ellipses from Points with
Applications to Circular Target Extraction in Images and Cylinder Detection
in Point Clouds
- URL: http://arxiv.org/abs/2011.13849v3
- Date: Tue, 30 Mar 2021 17:56:30 GMT
- Title: Robust Detection of Non-overlapping Ellipses from Points with
Applications to Circular Target Extraction in Images and Cylinder Detection
in Point Clouds
- Authors: Reza Maalek and Derek Lichti
- Abstract summary: This manuscript provides a collection of new methods for the automated detection of non-overlapping ellipses from edge points.
The methods introduce new developments in: (i) robust Monte Carlo-based ellipse fitting to 2-dimensional (2D) points in the presence of outliers; (ii) detection of non-overlapping ellipse from 2D edge points; and (iii) extraction of cylinder from 3D point clouds.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This manuscript provides a collection of new methods for the automated
detection of non-overlapping ellipses from edge points. The methods introduce
new developments in: (i) robust Monte Carlo-based ellipse fitting to
2-dimensional (2D) points in the presence of outliers; (ii) detection of
non-overlapping ellipse from 2D edge points; and (iii) extraction of cylinder
from 3D point clouds. The proposed methods were thoroughly compared with
established state-of-the-art methods, using simulated and real-world datasets,
through the design of four sets of original experiments. It was found that the
proposed robust ellipse detection was superior to four reliable robust methods,
including the popular least median of squares, in both simulated and real-world
datasets. The proposed process for detecting non-overlapping ellipses achieved
F-measure of 99.3% on real images, compared to F-measures of 42.4%, 65.6%, and
59.2%, obtained using the methods of Fornaciari, Patraucean, and Panagiotakis,
respectively. The proposed cylinder extraction method identified all detectable
mechanical pipes in two real-world point clouds, obtained under laboratory, and
industrial construction site conditions. The results of this investigation show
promise for the application of the proposed methods for automatic extraction of
circular targets from images and pipes from point clouds.
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