AQC0757

Nanopublication — Computational Image Analysis - AQC0757

by Arnaud Quercy · F Major - Research on Harmony - Variation 3 · 2024

Claim 1: Computational Image Analysis - AQC0757

The artwork F Major [1] - Research on Harmony - Variation 3 (AQC0757) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-02-04. 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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DDCBB4 34.3 yellow-orange wheat
2 151117 11.0 red-violet black
3 A59D93 10.4 yellow-orange steel gray
4 C2AAA2 8.7 orange steel gray
5 953456 8.5 red brown
6 E1DAD2 8.4 yellow-orange gainsboro
7 811E41 6.9 red firebrick
8 744226 5.2 orange russet
9 AD5271 3.4 red indianred
10 9C2118 3.2 red-orange russet

Color Families:

Family %
yellow-orange 53.1
red 18.8
orange 13.9
red-violet 11.0
red-orange 3.2

Texture Analysis

Metric Value
Global Roughness 0.274
Mean Local Roughness 0.014
Roughness Uniformity 0.016
Edge Density 0.06
Mean Gradient Magnitude 0.135
Gradient Variance 0.039
Gradient Smoothness 0.0
Directional Coherence 0.016
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.595
Spatial Variation 0.234
Texture Consistency 0.274

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.569
Brightness Variance 0.274
Brightness Uniformity 0.519
Brightness Skewness -0.559
Brightness Entropy 7.2
Rms Contrast 0.274
Michelson Contrast 1.0
Weber Contrast 0.855
Mean Local Contrast 0.017
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.784
Shadow Percentage 28.333
Midtone Percentage 20.746
Highlight Percentage 50.922
Shadow Clipping 0.005
Highlight Clipping 0.006
Tonal Balance 0.0
Fine Contrast 0.007
Medium Contrast 0.021
Coarse Contrast 0.036
Multiscale Contrast Ratio 0.179
Edge Contrast 0.135
Contrast Clustering 0.726

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.774
Color Clustering 0.767
Color Transition Smoothness 0.665
Transition Uniformity 0.753
Sharp Transition Ratio 0.1
Transition Directionality 0.021
Mean Saturation 0.319
Saturation Variance 0.064
Low Saturation Ratio 0.676
Medium Saturation Ratio 0.189
High Saturation Ratio 0.136
Saturation Clustering 0.999
Hue Concentration 0.792
Complementary Balance 0.001
Analogous Dominance 0.881
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 (2024). F Major - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0757.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/f-major-research-on-harmony-variation-3_8em.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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