A New RTI Portable Instrument for Surface Morphological Characterization
Abstract
:1. Introduction
2. Design
2.1. Global Description of the New RTI Instrument
- Berezhnoy et al. [39] showed that the brushstrokes are mainly oriented at 0°, 90° and 180°;
- Karimov et al. [40] studied the orientation of brushstrokes for several painters and showed that a lot of brushstrokes are oriented at 45° according to the painter (each painter has a personal gesture);
- The angle 45° is confirmed by Sablatnig et al. [41], as well as the angle 135°.
2.2. High-Resolution Imaging Functions
2.2.1. High Dynamic Range Mode
2.2.2. Focus Stacking Mode
2.2.3. Combination of Imaging Functions
3. Build Instructions
- Printing in 3D the monitoring box, the acquisition box, and the half-sphere using polylactic acid (PLA);
- Installing the lighting sources:
- Positioning the LEDs on the half-sphere and soldering them;
- Soldering connecting wires to the pins of the first LED (5V, ground and signal IN); the length of these wires depends on the length which is necessary between the acquisition system and the monitoring system.
- Installing the camera:
- Placing and fixing the camera into the acquisition box;
- Connecting the cables (4 connecting wires and 1 cable FPC) to the camera (the cables must have the same length than the LED wires).
- Installing the Raspberry OS for the use of the graphical interface:
- Mounting a microSD card (a minimum of 32GB is recommended) on a computer;
- Flashing the microSD card with the Raspberry Pi OS recommended by the software Raspberry Pi Imager (v1.8.5) and including a desktop;
- Inserting the flashed microSD on the Raspberry Pi card.
- Installing the components of the monitoring system into its box:
- Fixing the Raspberry card into the monitoring box;
- Fixing the Arduino card into the box;
- Placing the powerbank into the box;
- Fixing the screen on the box cover.
- Connecting the components:
- Passing the LED wires from the lighting half-sphere through a rigid cable (especially used to protect cables in situ) and connecting them to the Arduino pins;
- Passing the camera cables through the rigid cable and connecting them to the Raspberry card;
- Connecting the Arduino card to the Raspberry card;
- Connecting the screen to the Raspberry card;
- Connecting the powerbank to a switch and connecting the switch to the Raspberry card.
- Running the Raspberry system and updating it;
- Testing the camera and the LEDs using the scripts provided by the suppliers or manufacturers.
4. Operating Instructions
4.1. RTI Measurements
4.2. Generation of Geometrical Maps
4.3. Topographical and Statistical Analyses
4.4. Methodology Summary
5. Validation
5.1. Geometrical Maps
5.2. Reflectance Images
6. Conclusions
- MorphoLight is able to see a difference in painting strokes between two close color zones;
- The density of peaks, Spd, is higher for the sky part regarding the mean curvature maps due to a lot of fine brushstrokes;
- The fractal dimension highlights the difference between both painting zones at the whole scale range for high-resolution images (stacked and tonemapped) at a lighting position (θ, φ) = (30°, 225°). The sea part is more heterogeneous, rougher and has lower curvatures: the sky reflection on the sea is represented by large ripples;
- The high-resolution imaging functions, focus stacking and high dynamic range, improve the reflectance image quality and the topographical interpretation.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
Abbreviations | |
ANOVA | ANalysis Of VAriance |
CCD | Charge-Coupled Device |
CRF | Camera Response Function |
FS | Focus Stacking |
HDR | High Dynamic Range |
LDR | Low Dynamic Range |
NF | Normal Focus |
PLA | PolyLactic Acid |
RTI | Reflectance Transformation Imaging |
SGCLR | Surface Gradient Characterization by Light Reflectance |
XRF | X-ray Fluorescence |
Surface characterization parameters (3D) | |
S10z | Ten points height |
Sa | Arithmetic mean height |
Sdq | Root mean square gradient |
Sdr | Developed interfacial area ratio |
Sfd | Fractal dimension |
Spc | Arithmetic mean peak curvature |
Spd | Density of peaks |
Ssc | Arithmetic mean summit curvature |
Std | Texture direction |
Reflectance parameters | |
θ | Lighting elevation |
ρ | Maximum surface reflectance |
φ | Lighting azimuth |
H | Mean curvature |
I | Pixel intensity vector |
K | Curvature matrix |
K1 | Minimum principal curvature |
K2 | Maximum principal curvature |
Kg | Gaussian curvature |
KME | Mehlum curvature |
L | Lighting position matrix |
n | Normals |
Statistical parameters | |
F | Relevance value from ANOVA |
P95 | 95th percentile |
P5 | 5th percentile |
RI | Relevance index |
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Acquisition Mode | Benefits | Drawbacks |
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LDR/NF |
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LDR/FS |
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HDR/NF |
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HDR/FS |
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Type | Parameter | Name (Standard) | Description |
---|---|---|---|
Height | Sa | Arithmetic mean height (ISO 25178 [44]) | Mean height difference of each surface point compared to the mean surface plane |
Spatial | Std | Texture direction (ISO 25178) | Angular direction of the surface texture relative to the Y axis |
Hybrid | Sdq | Root mean square gradient (ISO 25178) | Mean value of the local surface slopes |
Hybrid | Sdr | Developed interfacial area ratio (ISO 25178) | Percentage of surface area added by the surface texture on an ideally smooth, flat surface |
Hybrid | Sfd | Fractal dimension (EUR 15178N [45]) | Regularity degree of a surface |
Hybrid | Ssc | Arithmetic mean summit 1 curvature (EUR 15178N) | Information on the shape and size of the high surface features (especially studied for surface contacts) |
Feature | Spd | Density of peaks (ISO 25178) | Number of peaks per unit of area |
Feature | Spc | Arithmetic mean peak 2 curvature (ISO 25178) | Information on the shape and size of the high surface features (especially studied for surface contacts) |
Feature | S10z | Ten points height (ISO 25178) | Sum of the mean height of the five highest peaks and the mean height of the five deepest valleys |
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Lemesle, J.; Bigerelle, M. A New RTI Portable Instrument for Surface Morphological Characterization. Hardware 2024, 2, 66-84. https://doi.org/10.3390/hardware2020004
Lemesle J, Bigerelle M. A New RTI Portable Instrument for Surface Morphological Characterization. Hardware. 2024; 2(2):66-84. https://doi.org/10.3390/hardware2020004
Chicago/Turabian StyleLemesle, Julie, and Maxence Bigerelle. 2024. "A New RTI Portable Instrument for Surface Morphological Characterization" Hardware 2, no. 2: 66-84. https://doi.org/10.3390/hardware2020004