Ellipse-fitting algorithm and adaptive threshold to eliminate outliers

Abstract

Terrestrial laser scanning is widely applied in many fields owing to its characteristic of rapid acquisition of massive 3D point data. It provides a new way to obtain the cross-section data of metro tunnels for deformation analysis. However, the data contain many outliers, such as pipe and bolt holes, and manual filtering of unwanted points is relatively onerous. Therefore, an ellipse-fitting algorithm based on residual p-norm minimum is proposed to deal with the outliers. Then, an adaptive threshold selection method is introduced for outlier elimination. The remaining valid data are utilised to calculate the deformation after data processing. The experiments validate that the p-norm minimum is more robust than the least-squares algorithm, and the application of an adaptive threshold allows the algorithm to clearly distinguish the outliers. This research provides a reference for the monitoring of subway tunnel deformation.

Keywords:

• Terrestrial laser scanning
• Metro tunnel
• P-norm minimum
• Adaptive threshold
• Deformation analysis

Additional information

Funding

This work was supported by National Natural Science Foundation of China (41671449).