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Integrating rotational components to optical properties observed in petrographic thin sections via automated image acquisition and analysis Cover

Integrating rotational components to optical properties observed in petrographic thin sections via automated image acquisition and analysis

Open Access
|Oct 2025

Figures & Tables

Figure 1.

Equation for calculating convexity. Convexity = (perimeter of A + B)/(perimeter of A).
Equation for calculating convexity. Convexity = (perimeter of A + B)/(perimeter of A).

Figure 2.

Workflow devised for this study. The ArcMap tools used are numbered and are as follow: (1) Colour Model Conversion function, (2) Composite Bands tool, (3) MFA, specifically the GSD tool, (4) Zonal Statistics tool, (5) Inbuilt raster calculator. GSD, grain size detector; MFA, micro fabric analyser; PPL, plane polarised light; RGB, red, green, blue; XPL, crossed polarised light.
Workflow devised for this study. The ArcMap tools used are numbered and are as follow: (1) Colour Model Conversion function, (2) Composite Bands tool, (3) MFA, specifically the GSD tool, (4) Zonal Statistics tool, (5) Inbuilt raster calculator. GSD, grain size detector; MFA, micro fabric analyser; PPL, plane polarised light; RGB, red, green, blue; XPL, crossed polarised light.

Figure 3.

Average interference colour images and MFA polygons for sample DRT 34 (A, B), sample A14 (C, D), sample D15 (E, F) and sample C20 (G, H). MFA, micro fabric analyser.
Average interference colour images and MFA polygons for sample DRT 34 (A, B), sample A14 (C, D), sample D15 (E, F) and sample C20 (G, H). MFA, micro fabric analyser.

Figure 4.

Average Interference colour image for sample A14 along with polygons produced from grain segmentation (A, B). Maximum Interference colour image for sample A14 along with polygons produced from grain segmentation (C, D). Minimum interference colour image for sample A14 along with polygons produced from grain segmentation (E, F).
Average Interference colour image for sample A14 along with polygons produced from grain segmentation (A, B). Maximum Interference colour image for sample A14 along with polygons produced from grain segmentation (C, D). Minimum interference colour image for sample A14 along with polygons produced from grain segmentation (E, F).

Figure 5.

Graphs showing the interference colour ranges (A) and the pleochroic colour ranges (B) for sample A14. (C) Graph showing the interference colour ranges for sample D15. HSV, hue, saturation and value.
Graphs showing the interference colour ranges (A) and the pleochroic colour ranges (B) for sample A14. (C) Graph showing the interference colour ranges for sample D15. HSV, hue, saturation and value.

Figure 6.

Interference based classification for sample A14 (A, B) and sample D15 (C, D) along with mineral proportions.
Interference based classification for sample A14 (A, B) and sample D15 (C, D) along with mineral proportions.

Figure 7.

The anorthite percentage for plagioclase grains in sample DRT 34 using both the Michel-Levy method and SEM analysis.
The anorthite percentage for plagioclase grains in sample DRT 34 using both the Michel-Levy method and SEM analysis.

Figure 8.

Grain shape classification for sample A14. (A) Grains classified as either elongated, equant or circular. (B) Grains classified as either euhedral, subhedral or anhedral. (C) The distribution of grains classified as elongated, equant or circular. (D) The distribution of grains classified as euhedral, subhedral or anhedral.
Grain shape classification for sample A14. (A) Grains classified as either elongated, equant or circular. (B) Grains classified as either euhedral, subhedral or anhedral. (C) The distribution of grains classified as elongated, equant or circular. (D) The distribution of grains classified as euhedral, subhedral or anhedral.

Figure 9.

Grain size distribution per mineral.
Grain size distribution per mineral.

Figure 10.

Grains classified based on size as either coarse-, medium- or fine-grained.
Grains classified based on size as either coarse-, medium- or fine-grained.

Figure 11.

Grain orientation with respect to the long axis for sample A14 plotted as rose diagrams. (A) Orientation of all grains within thin section. (B–D) Represent the orientation of the biotite, muscovite and quartz grains present.
Grain orientation with respect to the long axis for sample A14 plotted as rose diagrams. (A) Orientation of all grains within thin section. (B–D) Represent the orientation of the biotite, muscovite and quartz grains present.

Ranges used for classifying grains based on general proportions_

ShapeAsRCircularity
Elongated>1.6n/a
Equant<1.6<0.8
Circular<1.6>0.8

Ranges for classifying grains based on crystal shape_

ShapeConvexity
Euhedral>1.8
Subhedral<1.8
>1.7
Anhedral<1.7

Ranges for grouping grains based on size_

SizePixelscm2
Coarse>100,000>0.37
Medium<100,000, >10,000<0.37, >0.037
Fine<10,000<0.037

Microscope specifications_

ApplicationPlan UW
Magnification
Numerical aperture0.06
Lens image distance/coverslip thickness (mm)∞/−
Working distanceWD 7.5

Calculated extinction angles for biotite grains from sample A14_

Grain IDCalculated extinction angle
52425.5
54987.8
63204.6
43020.7
61238.7
61196.7
24145
21421.8
72552.3
19834.5
DOI: https://doi.org/10.2478/mipo-2025-0008 | Journal eISSN: 1899-8526 | Journal ISSN: 1899-8291
Language: English
Page range: 58 - 73
Submitted on: Mar 3, 2025
Accepted on: Sep 1, 2025
Published on: Oct 15, 2025
Published by: Mineralogical Society of Poland
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Jacob Johannes Pretorius, Matthew Jason Mayne, published by Mineralogical Society of Poland
This work is licensed under the Creative Commons Attribution 4.0 License.