AQC0565

Nanopublication — Computational Image Analysis - AQC0565

by Arnaud Quercy · Composition 1 · 2024

Claim 1: Computational Image Analysis - AQC0565

K-means clustering analysis [3] (10 colors) performed on artwork Composition [1] 1 (AQC0565) [2] by Arnaud Quercy [2] on 2026-02-04. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

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]: 1376x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 B9A5BB 16.5 red-violet steel gray
2 9A7A4F 14.5 yellow-orange burnt sienna
3 A894AC 14.4 red-violet steel gray
4 C0B6D0 12.1 violet silver
5 9C8097 10.6 red-violet dusty mauve
6 A9885E 9.3 yellow-orange peru
7 080B15 9.1 violet black
8 C7D3EA 7.4 blue-violet lightgray
9 945E76 3.8 red dusty mauve
10 742F4A 2.3 red dusty mauve
11 B6AC84 0.3 yellow ochre [Accent]

Color Families:

Family %
red-violet 41.4
yellow-orange 23.8
violet 21.2
blue-violet 7.4
red 6.2
yellow 0.3

Accent Colors:

Hex Family Name Chroma
B6AC84 yellow ochre 22.2

Texture Analysis

Metric Value
Global Roughness 0.201
Mean Local Roughness 0.032
Roughness Uniformity 0.03
Edge Density 0.168
Mean Gradient Magnitude 0.226
Gradient Variance 0.082
Gradient Smoothness 0.0
Directional Coherence 0.026
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.661
Spatial Variation 0.089
Texture Consistency 0.39

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.562
Brightness Variance 0.201
Brightness Uniformity 0.643
Brightness Skewness -1.345
Brightness Entropy 7.132
Rms Contrast 0.201
Michelson Contrast 1.0
Weber Contrast 0.667
Mean Local Contrast 0.031
Contrast Uniformity 0.055
Dynamic Range 1.0
Effective Dynamic Range 0.776
Shadow Percentage 11.041
Midtone Percentage 56.472
Highlight Percentage 32.487
Shadow Clipping 0.008
Highlight Clipping 0.002
Tonal Balance 0.0
Fine Contrast 0.019
Medium Contrast 0.039
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.226
Contrast Clustering 0.61

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.737
Color Clustering 0.849
Color Transition Smoothness 0.435
Transition Uniformity 0.462
Sharp Transition Ratio 0.1
Transition Directionality 0.028
Mean Saturation 0.299
Saturation Variance 0.043
Low Saturation Ratio 0.619
Medium Saturation Ratio 0.322
High Saturation Ratio 0.06
Saturation Clustering 0.998
Hue Concentration 0.468
Complementary Balance 0.057
Analogous Dominance 0.752
Temperature Bias 0.536

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). Composition 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0565.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/composition-1_6by.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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