Point cloud segmentation method for irregular parts based on Euclidean clustering

Min Guo; Jing Zhang; Yuanzhi Lyu; Zhenlan Li

doi:10.1117/12.3014781

4 March 2024 Point cloud segmentation method for irregular parts based on Euclidean clustering

Min Guo, Jing Zhang, Yuanzhi Lyu, Zhenlan Li

Proceedings Volume 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023); 1298128 (2024) https://doi.org/10.1117/12.3014781
Event: 9th International Symposium on Sensors, Mechatronics, and Automation (ISSMAS 2023), 2023, Nanjing, China

Abstract

In view of the problem of under-segmentation and over-segmentation in the point cloud segmentation process of irregular parts, a point cloud segmentation method for irregular parts based on Euclidean clustering is studied. First, the initial feature point extraction is performed based on the fast point feature histogram (FPFH); then the method of adjacent point angle and projection point angle is used to optimize the initial feature point extraction effect; finally, the threshold parameter is set, and the improved Euclidean clustering algorithm is used for clustering segmentation, and the clustering segmentation effect result graphs are obtained. The experimental results show that the algorithm can improve the segmentation accuracy of the irregular parts point cloud, not only ensure the integrity of each feature, but also enhance the processing of each feature detail part, and improve the speed of the clustering segmentation process.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Min Guo, Jing Zhang, Yuanzhi Lyu, and Zhenlan Li "Point cloud segmentation method for irregular parts based on Euclidean clustering", Proc. SPIE 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023), 1298128 (4 March 2024); https://doi.org/10.1117/12.3014781

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