Point Cloud Measurement of Rubber Tread Dimension Based on RGB-Depth Camera

To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a mathematical model of corner points and a reprojection error is established, and the optimal solution of the number of corner points is deter...

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Published in:	Applied sciences Vol. 14; no. 15; p. 6625
Main Authors:	Huang, Luobin, Chen, Mingxia, Peng, Zihao
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2024
Subjects:	Accuracy Algorithms Analysis Calibration Cameras Industrial production Measurement Measurement techniques non-dominated sorting genetic algorithm-II point cloud registration random sample consensus point cloud segmentation algorithm Research methodology RGB-depth Rubber tread size measurement
ISSN:	2076-3417, 2076-3417
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Abstract	To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a mathematical model of corner points and a reprojection error is established, and the optimal solution of the number of corner points is determined by the non-dominated sorting genetic algorithm II (NSGA-II), which reduces the reprojection error of the RGB-D camera. Secondly, to address the problem of the low accuracy of the traditional pixel metric ratio measurement method, the random sampling consensus point cloud segmentation algorithm (RANSAC) and the oriented bounding box (OBB) collision detection algorithm are introduced to complete the accurate detection of the tread size. By comparing the absolute error and relative error data of several groups of experiments, the accuracy of the detection method in this paper reaches 1 mm, and the measurement deviation is between 0.14% and 2.67%, which is in line with the highest accuracy standard of the national standard. In summary, the RGB-D visual inspection method constructed in this paper has the characteristics of low cost and high inspection accuracy, which is a potential solution to enhance the pickup guidance of tread size measurement.
AbstractList	To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a mathematical model of corner points and a reprojection error is established, and the optimal solution of the number of corner points is determined by the non-dominated sorting genetic algorithm II (NSGA-II), which reduces the reprojection error of the RGB-D camera. Secondly, to address the problem of the low accuracy of the traditional pixel metric ratio measurement method, the random sampling consensus point cloud segmentation algorithm (RANSAC) and the oriented bounding box (OBB) collision detection algorithm are introduced to complete the accurate detection of the tread size. By comparing the absolute error and relative error data of several groups of experiments, the accuracy of the detection method in this paper reaches 1 mm, and the measurement deviation is between 0.14% and 2.67%, which is in line with the highest accuracy standard of the national standard. In summary, the RGB-D visual inspection method constructed in this paper has the characteristics of low cost and high inspection accuracy, which is a potential solution to enhance the pickup guidance of tread size measurement.
Audience	Academic
Author	Peng, Zihao Chen, Mingxia Huang, Luobin
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Snippet	To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a...
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SubjectTerms	Accuracy Algorithms Analysis Calibration Cameras Industrial production Measurement Measurement techniques non-dominated sorting genetic algorithm-II point cloud registration random sample consensus point cloud segmentation algorithm Research methodology RGB-depth Rubber tread size measurement
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Title	Point Cloud Measurement of Rubber Tread Dimension Based on RGB-Depth Camera
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