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 in | Measurement science & technology Vol. 34; no. 10; p. 105006 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
01.10.2023
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| Online Access | Get full text |
| ISSN | 0957-0233 1361-6501 1361-6501 |
| DOI | 10.1088/1361-6501/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. |
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| 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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