Data-driven Laser Plane Optimization for High-precision Numerical Calibration of Line Structured Light Sensors

The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

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High precision calibration of line structured light sensors based on linear transformation over triangular domain

10.1117/12.2242945 ◽

2016 ◽

Cited By ~ 1

Author(s):

Yuehua Li ◽

Jingbo Zhou ◽

Fengshan Huang

Keyword(s):

High Precision ◽

Linear Transformation ◽

Structured Light ◽

Triangular Domain

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Research on Calibration Method of Linear Structured Light Vision Measurement System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.644-650.1234 ◽

2014 ◽

Vol 644-650 ◽

pp. 1234-1239

Author(s):

Tao He ◽

Yu Lang Xie ◽

Cai Sheng Zhu ◽

Jiu Yin Chen

Keyword(s):

High Precision ◽

Measurement System ◽

Structured Light ◽

Target Position ◽

Calibration Method ◽

Measurement Model ◽

Sensor Calibration ◽

Vision Measurement ◽

Set Up ◽

Structured Light Vision

This template explains and demonstrates how to design a measurement system based on the size of the linear structured light vision, the system could works at realized the high precision and fast measurement of the size of mechanical parts, and accurate calibration of the system. First of all, this paper set up the experimental platform based on linear structured light vision measurement. Secondly, this paper established a system of measurement model, and puts forward a new method of calibration of structured light sensor and set up the mathematical model of sensor calibration. This calibration method only need to use some gage blocks of high precision as the target, the target position need not have a strict requirements, and the solving process will be more convenient, much easier to field use and maintenance. Finally, measuring accuracy on the system by gage blocks with high precision is verified, the experiment shows that measurement accuracy within 0.050 mmin the depth of 0-80 - mm range. This system can satisfy the demands of precision testing of most industrial parts .with its simple calibration process and high precision, it is suitable for the structured light vision calibration.

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Development of a high-precision surface metrology system using structured light projection

Measurement ◽

10.1016/j.measurement.2005.07.014 ◽

2005 ◽

Vol 38 (3) ◽

pp. 236-247 ◽

Cited By ~ 58

Author(s):

Ming-June Tsai ◽

Chuan-Cheng Hung

Keyword(s):

High Precision ◽

Structured Light ◽

Surface Metrology ◽

Metrology System

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Improving Efficiency of Volunteer-Based Food Rescue Operations

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i08.7051 ◽

2020 ◽

Vol 34 (08) ◽

pp. 13369-13375

Author(s):

Zheyuan Ryan Shi ◽

Yiwen Yuan ◽

Kimberly Lo ◽

Leah Lizarondo ◽

Fei Fang

Keyword(s):

Food Insecurity ◽

High Precision ◽

Branch And Bound ◽

Food Waste ◽

Optimization Algorithm ◽

Data Driven ◽

Data Generation ◽

Rescue Operation ◽

Optimal Intervention ◽

Near Future

Food waste and food insecurity are two challenges that coexist in many communities. To mitigate the problem, food rescue platforms match excess food with the communities in need, and leverage external volunteers to transport the food. However, the external volunteers bring significant uncertainty to the food rescue operation. We work with a large food rescue organization to predict the uncertainty and furthermore to find ways to reduce the human dispatcher's workload and the redundant notifications sent to volunteers. We make two main contributions. (1) We train a stacking model which predicts whether a rescue will be claimed with high precision and AUC. This model can help the dispatcher better plan for backup options and alleviate their uncertainty. (2) We develop a data-driven optimization algorithm to compute the optimal intervention and notification scheme. The algorithm uses a novel counterfactual data generation approach and the branch and bound framework. Our result reduces the number of notifications and interventions required in the food rescue operation. We are working with the organization to deploy our results in the near future.

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Three-Dimensional Inner Surface Inspection System Based on Circle-Structured Light

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4041480 ◽

2018 ◽

Vol 140 (12) ◽

Cited By ~ 2

Author(s):

Zhu Ye ◽

Wang Lianpo ◽

Gu Yonggang ◽

Bi Songlin ◽

Zhai Chao ◽

...

Keyword(s):

Structured Light ◽

Three Dimensional ◽

Ccd Camera ◽

Absolute Error ◽

Surface Measurement ◽

Laser Triangulation ◽

Inspection System ◽

Surface Inspection ◽

Laser Plane ◽

Inner Surface

A three-dimensional (3D) inner surface inspection system is developed in this research based on circle-structured light, which is an improved laser triangulation method. A conical reflector is used to reflect the laser and generate radial laser plane that is called circle-structured light, and a CCD camera is used to capture the light stripe on the inner surface. Then, the 3D coordinates of points on the light stripe are calculated through laser triangulation algorithm. Compared with existing inner surface measurement systems, this research takes assembly errors and refraction distortion into consideration and proposes a laser plane mathematical model with four degrees-of-freedom along with corresponding flexible laser plane calibration technique based on binocular vision that is easy to operate. The proposed inspection system calibrated by proposed algorithm performs well in diameter measurement experiment, in which the absolute error is superior to 3 μm, and defect detecting experiment, in which the defect resolution is superior to 0.02 mm. Moreover, the system also performs well in straightness and roundness evaluation. Experiments indicate that this system is applicable in inner surface measurement and inspection, and the calibration method is accurate and easy to operate.

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Reliable and Accurate Wheel Size Measurement under Highly Reflective Conditions

Sensors ◽

10.3390/s18124296 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4296 ◽

Cited By ~ 1

Author(s):

Xiao Pan ◽

Zhen Liu ◽

Guangjun Zhang

Keyword(s):

High Precision ◽

Signal To Noise Ratio ◽

Structured Light ◽

Measurement Reliability ◽

Size Measurement ◽

Vision Sensor ◽

High Precision Measurement ◽

Measurement Framework ◽

Improve Measurement ◽

Structured Light Vision

Structured-light vision sensor, as an important tool for obtaining 3D data, is widely used in fields of online high-precision measurement. However, the captured stripe images can show high-dynamic characteristics of low signal-to-noise ratio and uneven brightness due to the complexity of the onsite environment. These conditions seriously affect measurement reliability and accuracy. In this study, a wheel size measurement framework based on a structured-light vision sensor, which has high precision and reliability and is suitable for highly reflective conditions, is proposed. Initially, the quality evaluation criterion of stripe images is established, and the entire stripe is distinguished into high- and low-quality segments. In addition, the multi-scale Retinex theory is adopted to enhance stripe brightness, which improves the reliability of subsequent stripe center extraction. Experiments verify that this approach can remarkably improve measurement reliability and accuracy and has important practical value.

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Adaptive Structured Light with Scatter Correction for High-Precision Underwater 3D Measurements

Sensors ◽

10.3390/s19051043 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1043 ◽

Cited By ~ 2

Author(s):

Petter Risholm ◽

Trine Kirkhus ◽

Jens Thielemann ◽

Jostein Thorstensen

Keyword(s):

High Precision ◽

Structured Light ◽

Scatter Correction ◽

Gray Code ◽

Forward Scatter ◽

Phase Stepping ◽

Accuracy And Precision ◽

Phase Unwrap ◽

Phase Estimate ◽

Frequency Phase

High-precision underwater 3D cameras are required to automate many of the traditional subsea inspection, maintenance and repair (IMR) operations. In this paper we introduce a novel multi-frequency phase stepping (structured light) method for high-precision 3D estimation even in turbid water. We introduce an adaptive phase-unwrapping procedure which uses the phase-uncertainty to determine the highest frequency that can be reliably unwrapped. Light scattering adversely affects the phase estimate. We propose to remove the effect of forward scatter with an unsharp filter and a model-based method to remove the backscatter effect. Tests in varying turbidity show that the scatter correction removes the adverse effect of scatter on the phase estimates. The adaptive frequency unwrapping with scatter correction results in images with higher accuracy and precision and less phase unwrap errors than the Gray-Code Phase Stepping (GCPS) approach.

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