JOURNAL ARTICLE

Fast 3D Object Measurement Based on Point Cloud Modeling.

  • Published In: International Journal of Pattern Recognition & Artificial Intelligence, 2023, v. 37, n. 11. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wang, Gang; Zhou, Mingliang; Fang, Bin; Zhang, Yugui; Guan, Shouqin; Ruan, Bin; Li, Zelin 3 of 3

Abstract

Automated object measurement is becoming increasingly important due to its ability to reduce manual costs, increase production efficiency, and minimize errors in various fields. In this paper, we present a novel approach to three-dimensional (3D) object measurement based on point cloud modeling. Our method introduces a fast point cloud modeling computation framework consisting of five stages: coordinate centralization, rotation and translation, noise filtering, plane projection, and geometric computation. Furthermore, we propose a fast convex hull optimization algorithm to reduce the high complexity problem of traditional convex hull calculation. Our extensive experiments demonstrate that our approach outperforms existing methods in terms of measurement error rate and time savings, with a maximum time saving of 31.03% under certain error conditions. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Pattern Recognition & Artificial Intelligence. 2023/09, Vol. 37, Issue 11, p1
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2023
  • ISSN:0218-0014
  • DOI:10.1142/S0218001423550133
  • Accession Number:172435024
  • Copyright Statement:Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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