AQC0877

Nanopublication — Computational Image Analysis - AQC0877

by Arnaud Quercy · E Minor - Research on Harmony - Variations 6 · 2025

Claim 1: Computational Image Analysis - AQC0877

The artwork E Minor [1] - Research on Harmony - Variations 6 (AQC0877) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2025-12-11. Method: k-means clustering with 10 colors extracted. Metrics documented: color distribution, texture analysis, brightness/contrast, spatial patterns.

Context

Analysis performed according to MMIDS-CMP-2025 [3] includes four metric categories: (1) Color distribution via k-means (10 colors), (2) Texture analysis using Haralick features, (3) Brightness and contrast measurements, (4) Spatial pattern characterization. Source image [5]: 1918x2877 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 E5B223 15.8 yellow-orange goldenrod
2 E6A34F 14.9 orange sandybrown
3 EAB16A 14.9 orange darksalmon
4 E7E0BE 13.9 yellow wheat
5 EFBF83 11.9 orange burlywood
6 524A3E 8.4 yellow-orange dark brown
7 CBDA67 7.7 yellow-green ochre
8 EAD150 6.2 yellow ochre
9 ED8B14 3.8 orange darkorange
10 8F7E64 2.6 yellow-orange gray

Color Families:

Family %
orange 45.4
yellow-orange 26.8
yellow 20.1
yellow-green 7.7

Texture Analysis

Metric Value
Global Roughness 0.151
Mean Local Roughness 0.019
Roughness Uniformity 0.023
Edge Density 0.054
Mean Gradient Magnitude 0.163
Gradient Variance 0.058
Gradient Smoothness 0.0
Directional Coherence 0.012
Pattern Complexity 0.11
Pattern Repetition 1.0
Detail Frequency Ratio 0.621
Spatial Variation 0.096
Texture Consistency 0.615

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.705
Brightness Variance 0.151
Brightness Uniformity 0.786
Brightness Skewness -1.656
Brightness Entropy 6.791
Rms Contrast 0.151
Michelson Contrast 1.0
Weber Contrast 0.384
Mean Local Contrast 0.022
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.569
Shadow Percentage 5.857
Midtone Percentage 14.841
Highlight Percentage 79.302
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.011
Medium Contrast 0.027
Coarse Contrast 0.044
Multiscale Contrast Ratio 0.242
Edge Contrast 0.163
Contrast Clustering 0.385

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.762
Color Clustering 0.366
Color Transition Smoothness 0.595
Transition Uniformity 0.613
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.536
Saturation Variance 0.057
Low Saturation Ratio 0.213
Medium Saturation Ratio 0.564
High Saturation Ratio 0.223
Saturation Clustering 0.999
Hue Concentration 0.981
Complementary Balance 0.0
Analogous Dominance 0.999
Temperature Bias 0.885

Methodology

This analysis employs standardized computational methods for objective image characterization. Color extraction uses k-means clustering algorithm. Texture analysis applies Haralick feature extraction. Brightness metrics include mean, variance, and distribution analysis. Spatial patterns are characterized through coherence and clustering measurements. All methods are deterministic and reproducible. Analysis performed by Multimodal Institute's computational imaging systems.

References

[1] Arnaud Quercy (2025). E Minor - Research on Harmony - Variations 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0877.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/11/e-minor-research-on-harmony-variations-6_i21.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/11/mmids-cmp-2025-computational-image-analysis-standard-dg1.html

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

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