AQC0479

Nanopublication — Computational Image Analysis - AQC0479

Claim 1: Computational Image Analysis - AQC0479

K-means clustering analysis [3] (10 colors) performed on artwork Luigi [1] (AQC0479) [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]: 1536x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 8A8C63 14.1 yellow gray
2 9DAA91 12.2 yellow-green darkseagreen
3 4F3425 11.9 orange dark brown
4 676249 11.9 yellow dimgray
5 6FC0DB 11.7 blue skyblue
6 93DEEF 8.7 blue-green lightskyblue
7 5E7977 7.8 green dimgrey
8 519DBC 7.6 blue steelblue
9 305154 7.5 blue-green darkslategray
10 C0D4BA 6.6 yellow-green silver
11 450B07 0.3 red-orange very dark red [Accent]
12 2E9BD7 0.3 blue-violet dodgerblue [Accent]
13 BE9A6C 0.3 yellow-orange ochre [Accent]

Color Families:

Family %
yellow 26.0
blue 19.3
yellow-green 18.8
blue-green 16.2
orange 11.9
green 7.8
red-orange 0.3
blue-violet 0.3
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
450B07 red-orange very dark red 31.9
2E9BD7 blue-violet dodgerblue 40.3
BE9A6C yellow-orange ochre 29.8

Texture Analysis

Metric Value
Global Roughness 0.193
Mean Local Roughness 0.079
Roughness Uniformity 0.035
Edge Density 0.387
Mean Gradient Magnitude 0.536
Gradient Variance 0.134
Gradient Smoothness 0.318
Directional Coherence 0.006
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.717
Spatial Variation 0.089
Texture Consistency 0.787

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.523
Brightness Variance 0.193
Brightness Uniformity 0.631
Brightness Skewness -0.078
Brightness Entropy 7.588
Rms Contrast 0.193
Michelson Contrast 1.0
Weber Contrast 0.675
Mean Local Contrast 0.075
Contrast Uniformity 0.589
Dynamic Range 1.0
Effective Dynamic Range 0.62
Shadow Percentage 20.586
Midtone Percentage 52.9
Highlight Percentage 26.514
Shadow Clipping 0.002
Highlight Clipping 0.001
Tonal Balance 0.334
Fine Contrast 0.046
Medium Contrast 0.091
Coarse Contrast 0.094
Multiscale Contrast Ratio 0.492
Edge Contrast 0.536
Contrast Clustering 0.213

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.692
Color Clustering 0.7
Color Transition Smoothness 0.0
Transition Uniformity 0.166
Sharp Transition Ratio 0.1
Transition Directionality 0.007
Mean Saturation 0.373
Saturation Variance 0.036
Low Saturation Ratio 0.371
Medium Saturation Ratio 0.579
High Saturation Ratio 0.05
Saturation Clustering 0.996
Hue Concentration 0.32
Complementary Balance 0.117
Analogous Dominance 0.5
Temperature Bias -0.268

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 (2023). Luigi — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0479.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/luigi_5ei.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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