Sharp Feature Detection as a Useful Tool in Smart Manufacturing

Author:

Prochazkova JanaORCID,Procházka DavidORCID,Landa JaromírORCID

Abstract

Industry 4.0 comprises a wide spectrum of developmental processes within the management of manufacturing and chain production. Presently, there is a huge effort to automate manufacturing and have automatic control of the production. This intention leads to the increased need for high-quality methods for digitization and object reconstruction, especially in the area of reverse engineering. Commonly used scanning software based on well-known algorithms can correctly process smooth objects. Nevertheless, they are usually not applicable for complex-shaped models with sharp features. The number of the points on the edges is extremely limited due to the principle of laser scanning and sometimes also low scanning resolution. Therefore, a correct edge reconstruction problem occurs. The same problem appears in many other laser scanning applications, i.e., in the representation of the buildings from airborne laser scans for 3D city models. We focus on a method for preservation and reconstruction of sharp features. We provide a detailed description of all three key steps: point cloud segmentation, edge detection, and correct B-spline edge representation. The feature detection algorithm is based on the conventional region-growing method and we derive the optimal input value of curvature threshold using logarithmic least square regression. Subsequent edge representation stands on the iterative algorithm of B-spline approximation where we compute the weighted asymmetric error using the golden ratio. The series of examples indicates that our method gives better or comparable results to other methods.

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Efficient Global Constraint Approach for Robust Contour Feature Points Extraction of Point Cloud;IEEE Transactions on Geoscience and Remote Sensing;2023

2. Geometric mistuning identification and finite element model updating methods for bladed disks;Aerospace Science and Technology;2022-11

3. Implementation of AHP Methodology for the Evaluation and Selection Process of a Reverse Engineering Scanning System;Applied Sciences;2021-12-17

4. Analysis of Data Point Cloud Preprocessing and Feature Angle Detection Algorithm;Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering);2021-12-10

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