Measurement point cloud registration method for complex mechanical parts based on improved ICP

Jiakang Ma; Jigang Wu; Kang Yang

doi:10.1117/12.2667168

27 January 2023 Measurement point cloud registration method for complex mechanical parts based on improved ICP

Jiakang Ma, Jigang Wu, Kang Yang

Proceedings Volume 12550, International Conference on Optical and Photonic Engineering (icOPEN 2022); 1255005 (2023) https://doi.org/10.1117/12.2667168
Event: International Conference on Optical and Photonic Engineering (icOPEN 2022), 2022, ONLINE, China

Abstract

Point cloud registration is the key step of 3D non-contact precision measurement for complex mechanical parts based on machine vision. Due to extreme dependence on initial position, slow iterative convergence and many wrong corresponding point pairs, Iterative Closest Point (ICP) algorithm could not satisfy the requirements of point cloud registration efficiency and precision for measurement of large quantities of complex mechanical parts, so an improved ICP method of measurement point cloud registration for complex mechanical parts by combining ICP with Intrinsic Shape Signature-Fast Point Feature Histogram (ISS-FPFH) feature is proposed. In order to reduce the registration quantity of the point cloud and keep the original subtle features on surface of point cloud, the voxel filter based on the point close to center of gravity is proposed to preprocess for point cloud down sampling. It is difficult for traditional ICP algorithm to determine the appropriate initial position and will lead to the registration failure of multi-view measurement point cloud, the Sample Consensus Initial Registration (SAC-IA) algorithm based on ISS-FPFH is applied for coarse registration. In order to solve the problems of slow iterative convergence and many wrong corresponding point pairs of traditional ICP algorithm, the point-to-plane ICP algorithm by combining with normal vector angle constraint is proposed for fine registration. Through experimental comparison and analysis, the results show that the accuracy and efficiency of the method proposed in this paper can meet requirements of 3D non-contact precision measurement for large quantities of complex mechanical parts.

Citation Download Citation

Jiakang Ma, Jigang Wu, and Kang Yang "Measurement point cloud registration method for complex mechanical parts based on improved ICP", Proc. SPIE 12550, International Conference on Optical and Photonic Engineering (icOPEN 2022), 1255005 (27 January 2023); https://doi.org/10.1117/12.2667168

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Point clouds

Image registration

Voxels

3D metrology

Precision measurement

Mechanical efficiency

3D modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years