AQC0804

Nanopublication — Computational Image Analysis - AQC0804

by Arnaud Quercy · Bb Octaves - Reflexions 30 · 2024

Claim 1: Computational Image Analysis - AQC0804

The artwork Bb Octaves [1] - Reflexions 30 (AQC0804) [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]: 2384x3576 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 92929E 16.1 violet lightslategray
2 A4A1A5 15.4 gray steel gray
3 C6C4B8 15.3 yellow silver
4 C0C6CB 13.7 white lightgray
5 848493 12.6 violet dusty mauve
6 B6B6B3 10.9 gray steel gray
7 796582 5.1 red-violet dusty mauve
8 5B555E 4.3 red-violet dusty mauve
9 5E7A80 3.6 blue-green blue gray
10 36363B 2.9 gray dusty mauve

Color Families:

Family %
gray 29.2
violet 28.8
yellow 15.3
white 13.7
red-violet 9.5
blue-green 3.6

Texture Analysis

Metric Value
Global Roughness 0.143
Mean Local Roughness 0.01
Roughness Uniformity 0.011
Edge Density 0.03
Mean Gradient Magnitude 0.089
Gradient Variance 0.018
Gradient Smoothness 0.0
Directional Coherence 0.061
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.601
Spatial Variation 0.101
Texture Consistency 0.46

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.62
Brightness Variance 0.143
Brightness Uniformity 0.77
Brightness Skewness -0.851
Brightness Entropy 6.863
Rms Contrast 0.143
Michelson Contrast 1.0
Weber Contrast 0.455
Mean Local Contrast 0.011
Contrast Uniformity 0.0
Dynamic Range 0.945
Effective Dynamic Range 0.443
Shadow Percentage 4.459
Midtone Percentage 53.452
Highlight Percentage 42.088
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.014
Coarse Contrast 0.024
Multiscale Contrast Ratio 0.235
Edge Contrast 0.089
Contrast Clustering 0.54

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.749
Color Clustering 0.915
Color Transition Smoothness 0.77
Transition Uniformity 0.874
Sharp Transition Ratio 0.1
Transition Directionality 0.076
Mean Saturation 0.101
Saturation Variance 0.006
Low Saturation Ratio 0.968
Medium Saturation Ratio 0.032
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.708
Complementary Balance 0.001
Analogous Dominance 0.625
Temperature Bias -0.377

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). Bb Octaves - Reflexions 30 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0804.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/bb-octaves-reflexions-30_8ww.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/10/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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