A 3D Matching Method to Compare a Scan to Its Reference using 3D Registration and Monte Carlo Metropolis Hastings Optimization for Industrial Inspection Applications

Clément Dubosq, Andréa Guerrero

2022

Abstract

Currently in industry, inspection tasks are essential to ensure a product efficacity and reliability. Some automated tools to inspect, i.e. to detect defect exist, but they are not adapted to an industrial inspection application. Most of industrial inspection is human made. In this article, we propose a new algorithm to match a 3D point-cloud to its 3D reference to track visual defects. First, we reconstruct a 3D model of an object using Iterative Closest Points (ICP) algorithm. Then, we propose an ICP initialization based on a Monte Carlo Metropolis-Hasting optimization to match a partial point-cloud to its model. We applied our algorithm to the data measured from a Time-of-Flight sensor and a RGB camera. We present the results and performance of this approach for objects of different complexities and sizes. The proposed methodology shows good results and adaptability compared to a state-of-the-art method called Go-ICP.

Paper Citation

in Harvard Style

Dubosq C. and Guerrero A. (2022). A 3D Matching Method to Compare a Scan to Its Reference using 3D Registration and Monte Carlo Metropolis Hastings Optimization for Industrial Inspection Applications. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-549-4, pages 518-525. DOI: 10.5220/0010779100003122

in Bibtex Style

@conference{icpram22,
author={Clément Dubosq and Andréa Guerrero},
title={A 3D Matching Method to Compare a Scan to Its Reference using 3D Registration and Monte Carlo Metropolis Hastings Optimization for Industrial Inspection Applications},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2022},
pages={518-525},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010779100003122},
isbn={978-989-758-549-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A 3D Matching Method to Compare a Scan to Its Reference using 3D Registration and Monte Carlo Metropolis Hastings Optimization for Industrial Inspection Applications
SN - 978-989-758-549-4
AU - Dubosq C.
AU - Guerrero A.
PY - 2022
SP - 518
EP - 525
DO - 10.5220/0010779100003122