A Novel Camera-Based Measurement System for Roughness Determination of Concrete Surfaces
Abstract
:1. Introduction
- Fully digital measurement system and reproducibility of results.
- Contactless and area-based measurement.
- Deployable on construction sites and high mobility.
- Applicability on arbitrary oriented surfaces.
- Easy to use.
- Lightweight.
- Low-cost.
2. State of the Art and Related Work
3. Theoretical Background
3.1. Defining Roughness
3.1.1. Shape Deviations
3.1.2. Parameters
Arithmetical Mean Deviation of the Assessed Profile ()
Mean Texture Depth ()
3.2. Digital Photogrammetry
3.2.1. Camera Model
3.2.2. Epipolar Geometry
4. Measurement System
4.1. Concept for Image Capture
4.2. Apparatus
4.3. Custom-Built 3D Calibration Test-Field
5. Methodology
5.1. 3D Reconstruction Pipeline
5.1.1. Preprocessing
5.1.2. Structure from Motion
5.1.3. Dense Image Matching
- A
- Cost Initialization:
- B
- Cost Aggregation:
- C
- Disparity Selection:
Disparity Map Fusion and Point Cloud Generation
5.2. Adapting Roughness Parameter to 3D Point Clouds
Arithmetical Mean Deviation
6. Experiments
6.1. Camera Calibration
6.1.1. Self-Calibration
6.1.2. Calibration of the Test-Field
6.1.3. Calibration of the Industrial Camera
6.2. System Assessment
6.2.1. Test Objects
6.2.2. Measurement Procedure
7. Results and Discussion
7.1. GPU Acceleration of SGM
7.2. Comparison of the Results of Our Measurement System with the Sand Patch Method
7.3. Area- vs. Line-Based Estimation of the Roughness
8. Conclusions
8.1. Summary
8.2. Outlook
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Shape Deviations | ||
---|---|---|
1. Order Form deviation | Curvature, Unevenness | |
2. Order Waviness | Waves | |
3. Order Roughness | Grooves | |
4. Order Roughness | Ridges, Scales, Crests | |
5. Order Roughness | Microstructure of the material | not easily presentable in image form |
6. Order | Lattice structure of the material | not easily presentable in image form |
Specification | Value |
---|---|
Resolution (H × V) | 3840 pixel × 2748 pixel |
Pixel size (H × V) | 1.67 µm × 1.67 µm |
Bit depth | 12 bits |
Signal-to-noise ratio | 32.9 dB |
Mono/Colour | Mono |
Shutter technology | Rolling shutter |
1.00 | −0.06 | 0.15 | −1.00 | 0.99 | −0.97 | 0.22 | 0.13 | |
1.00 | 0.05 | 0.06 | −0.06 | 0.06 | 0.04 | 0.01 | ||
1.00 | −0.15 | 0.14 | −0.13 | 0.04 | −0.02 | |||
1.00 | −0.99 | 0.97 | −0.22 | −0.13 | ||||
1.00 | −0.99 | 0.22 | 0.13 | |||||
1.00 | −0.21 | −0.13 | ||||||
1.00 | 0.03 | |||||||
1.00 |
Parameter | Value | Std. Dev. | |
---|---|---|---|
8.2545 mm | 0.0007 mm | ||
0.0737 mm | 0.0012 mm | ||
0.0051 mm | 0.0007 mm | ||
−43.8231 | 0.2449 | ||
565.8091 | 36.7678 | ||
−10,555.4693 | 1665.3598 | ||
5.1708 | 0.2624 | ||
10.2455 | 0.2549 |
1.00 | 0.00 | 0.01 | 0.03 | −0.01 | 0.00 | 0.00 | 0.00 | |
1.00 | 0.00 | −0.01 | 0.01 | −0.01 | 0.72 | 0.00 | ||
1.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.38 | |||
1.00 | −0.98 | 0.93 | 0.01 | 0.00 | ||||
1.00 | −0.99 | −0.01 | 0.00 | |||||
1.00 | 0.01 | 0.00 | ||||||
1.00 | 0.00 | |||||||
1.00 |
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Özcan, B.; Schwermann, R.; Blankenbach, J. A Novel Camera-Based Measurement System for Roughness Determination of Concrete Surfaces. Materials 2021, 14, 158. https://doi.org/10.3390/ma14010158
Özcan B, Schwermann R, Blankenbach J. A Novel Camera-Based Measurement System for Roughness Determination of Concrete Surfaces. Materials. 2021; 14(1):158. https://doi.org/10.3390/ma14010158
Chicago/Turabian StyleÖzcan, Barış, Raimund Schwermann, and Jörg Blankenbach. 2021. "A Novel Camera-Based Measurement System for Roughness Determination of Concrete Surfaces" Materials 14, no. 1: 158. https://doi.org/10.3390/ma14010158
APA StyleÖzcan, B., Schwermann, R., & Blankenbach, J. (2021). A Novel Camera-Based Measurement System for Roughness Determination of Concrete Surfaces. Materials, 14(1), 158. https://doi.org/10.3390/ma14010158