Research on Measurement Method of Tread Pattern Groove Depth Based on Computer Vision and Structured Light Measurement Technology

2021 ◽  
Author(s):  
Kang Wang ◽  
Guangyuan Zhang ◽  
Lijuan Xu ◽  
Xiaonan Gao
Keyword(s):  
Computer Vision ◽  
Measurement Method ◽  
Structured Light ◽  
Groove Depth ◽  
Measurement Technology ◽  
Light Measurement

scholarly journals A New Calibration Method of the Projector in Structured Light Measurement Technology

Procedia CIRP ◽  
2015 ◽  
Vol 27 ◽  
pp. 303-308 ◽  
Author(s):  
Zhen Lei ◽  
Xiaojun Liu ◽  
Wenlong Lu ◽  
Zili Lei ◽  
Liangzhou Chen ◽  
...  
Keyword(s):  
Structured Light ◽  
Calibration Method ◽  
Measurement Technology ◽  
Light Measurement

Multi-View Registration Based on Triangle Constraint and Global Optimization

2014 ◽  
Vol 722 ◽  
pp. 327-333
Author(s):  
Rong Hua Wang ◽  
Hua Zhang ◽  
Feng Xu ◽  
Li Yue
Keyword(s):  
Global Optimization ◽  
Measurement Error ◽  
Least Squares ◽  
Marked Point ◽  
Structured Light ◽  
3D Scanning ◽  
Measurement Technology ◽  
Automatic Registration ◽  
Light Measurement ◽  
Automation Level

The measurement technology of 3D scanning in automation level is low, its measurement process is not stable, and the measurement error is large. After the principle of binocular structured light measurement was analyzed, match the marked point to multi-view registration based on the relative distance of any two marked point in space is unchanged. A multi-view registration is proposed using triangle constraint and global optimization. The method includes: remove the false matching points in possible matching points by joining triple constraint; after the first registration, use the center of marking points to global optimization through least squares principle method. The realization of the algorithm by use of tools such as VC++ and Open CV demonstrates that this method has the advantage of better restraining the accumulative error, keeping the process stable, and fast and realizing automatic registration.

scholarly journals Non-Contact Respiration Measurement Method Based on RGB Camera Using 1D Convolutional Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3456
Author(s):  
Hyeon-Sang Hwang ◽  
Eui-Chul Lee
Keyword(s):  
Measurement Method ◽  
Respiratory Diseases ◽  
Region Of Interest ◽  
Average Error ◽  
Measurement Technology ◽  
Altman Analysis ◽  
Clinical Scenarios ◽  
Actual Environment ◽  
Error Bias ◽  
Robust To Noise

Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would reduce discomfort and help detect and prevent fatal diseases. Therefore, we propose a respiration measurement method using a learning-based region-of-interest detector and a clustering-based respiration pixel estimation technique. The proposed method consists of a model for classifying whether a pixel conveys respiration information based on its variance and a method for classifying pixels with clear breathing components using the symmetry of the respiration signals. The proposed method was evaluated with the data of 14 men and women acquired in an actual environment, and it was confirmed that the average error was within approximately 0.1 bpm. In addition, a Bland–Altman analysis confirmed that the measurement result had no error bias, and regression analysis confirmed that the correlation of the results with the reference is high. The proposed method, designed to be inexpensive, fast, and robust to noise, is potentially suitable for practical use in clinical scenarios.

A rail wear measurement method based on structured light scanning

2017 ◽  
Author(s):  
Peng Chen ◽  
Peijun Wang ◽  
Martin Lauer ◽  
Xiaomin Tang ◽  
Jindong Wang
Keyword(s):  
Measurement Method ◽  
Structured Light ◽  
Rail Wear ◽  
Wear Measurement ◽  
Structured Light Scanning

The Study on High Precision 3D Detection Method of Steel Plate Surface Based on Structured Light

2012 ◽  
Vol 572 ◽  
pp. 338-342 ◽  
Author(s):  
Zhi Guo Liang ◽  
Quan Yang ◽  
Ke Xu ◽  
Fei He ◽  
Xiao Chen Wang ◽  
...  
Keyword(s):  
Surface Quality ◽  
Steel Plate ◽  
Detection Method ◽  
Structured Light ◽  
Detection Methods ◽  
Measurement Technology ◽  
Detection Accuracy ◽  
Plate Surface ◽  
Factors Affecting

Structured light 3D measurement technology with its simple structure, non-contact measurement, fast measurement speed and other advantages, has been widely used. Steel plate surface quality detection is not confined to the two-dimensional feature of gray detection, and local topography measurement for surface quality of steel plate detection becomes increasingly important. In this paper, steel plate surface 3D detection method based on structured light and the factors affecting the measurement accuracy are analyzed. Several effective methods of improving 3D detection accuracy are put forward. Compared with the traditional structured light 3D detection methods, the detection accuracy of new methods is remarkably improved, thus possessing better application values.

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