Multi-angle 3D measurement of small workpieces using EDMS algorithm

Binocular vision can get the three-dimensional information of the objects according to two-dimensional images. However, when the background texture information of the workpiece to be measured is weak, or the depth information cannot be recognized due to the change of viewing angle, it will lead to p...

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Published inMeasurement science & technology Vol. 34; no. 10; p. 105006
Main Authors Song, Kun, Yi, Huaian, Lieping, Zhang, Lei, Jing, Huang, Jiefeng
Format Journal Article
LanguageEnglish
Published 01.10.2023
Online AccessGet full text
ISSN0957-0233
1361-6501
1361-6501
DOI10.1088/1361-6501/acdf0a

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Abstract Binocular vision can get the three-dimensional information of the objects according to two-dimensional images. However, when the background texture information of the workpiece to be measured is weak, or the depth information cannot be recognized due to the change of viewing angle, it will lead to poor three-dimensional measurement accuracy. To address this problem, the paper proposes a multi-view workpiece 3D measurement method based on binocular vision. First, an experimental bench with a Chessboard is designed. The corner point reconstruction is realized by extracting the corner point of the calibration plate. The checkerboard plane is fitted by the least squares method to obtain the checkerboard plane mathematical model. Then, the vertices of the workpiece are extracted at the subpixel level, and a minimum distance sparse vertex stereo matching algorithm (EDMS) based on Euclidean distance metric is proposed to achieve accurate and fast corner matching. Finally, the three-dimensional dimensions of the workpiece are calculated. Through experiments on multiple angles of the two workpieces, the results show that the average absolute error measured by the method at different angles is 0.33 mm, the total relative error is 0.90%, and the variance is less than that 0.01 mm 2 , realizing the more accurate measurement of multi-view three-dimensional dimensions of small workpieces. This paper provides a new binocular vision handheld mobile 3D measurement equipment method.
AbstractList Binocular vision can get the three-dimensional information of the objects according to two-dimensional images. However, when the background texture information of the workpiece to be measured is weak, or the depth information cannot be recognized due to the change of viewing angle, it will lead to poor three-dimensional measurement accuracy. To address this problem, the paper proposes a multi-view workpiece 3D measurement method based on binocular vision. First, an experimental bench with a Chessboard is designed. The corner point reconstruction is realized by extracting the corner point of the calibration plate. The checkerboard plane is fitted by the least squares method to obtain the checkerboard plane mathematical model. Then, the vertices of the workpiece are extracted at the subpixel level, and a minimum distance sparse vertex stereo matching algorithm (EDMS) based on Euclidean distance metric is proposed to achieve accurate and fast corner matching. Finally, the three-dimensional dimensions of the workpiece are calculated. Through experiments on multiple angles of the two workpieces, the results show that the average absolute error measured by the method at different angles is 0.33 mm, the total relative error is 0.90%, and the variance is less than that 0.01 mm 2 , realizing the more accurate measurement of multi-view three-dimensional dimensions of small workpieces. This paper provides a new binocular vision handheld mobile 3D measurement equipment method.
Author Huang, Jiefeng
Lieping, Zhang
Song, Kun
Lei, Jing
Yi, Huaian
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