AQC0542

Nanopublication — Computational Image Analysis - AQC0542

by Arnaud Quercy · Meditations · 2024

Claim 1: Computational Image Analysis - AQC0542

K-means clustering analysis [3] (10 colors) performed on artwork Meditations [1] (AQC0542) [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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 C5AC8F 18.1 orange tan
2 BBA084 17.8 orange rosybrown
3 4E3133 13.7 red-orange darkslategray
4 D1B99C 12.7 yellow-orange burlywood
5 B09377 12.0 orange ochre
6 5D3F40 10.7 red-orange dark brown
7 A08269 5.6 orange gray
8 E1CCAE 5.4 yellow-orange wheat
9 715351 3.5 red-orange dimgray
10 20100B 0.5 red-orange black
11 325973 0.3 blue grayish purple [Accent]
12 0E1737 0.3 violet very dark purple [Accent]

Color Families:

Family %
orange 53.5
red-orange 28.4
yellow-orange 18.0
blue 0.3
violet 0.3

Accent Colors:

Hex Family Name Chroma
325973 blue grayish purple 19.9
0E1737 violet very dark purple 23.4

Texture Analysis

Metric Value
Global Roughness 0.197
Mean Local Roughness 0.009
Roughness Uniformity 0.005
Edge Density 0.009
Mean Gradient Magnitude 0.085
Gradient Variance 0.006
Gradient Smoothness 0.078
Directional Coherence 0.03
Pattern Complexity 0.112
Pattern Repetition 1.0
Detail Frequency Ratio 0.588
Spatial Variation 0.178
Texture Consistency 0.492

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.556
Brightness Variance 0.197
Brightness Uniformity 0.646
Brightness Skewness -0.708
Brightness Entropy 6.945
Rms Contrast 0.197
Michelson Contrast 1.0
Weber Contrast 0.675
Mean Local Contrast 0.01
Contrast Uniformity 0.39
Dynamic Range 0.988
Effective Dynamic Range 0.557
Shadow Percentage 25.566
Midtone Percentage 35.781
Highlight Percentage 38.653
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.012
Coarse Contrast 0.022
Multiscale Contrast Ratio 0.213
Edge Contrast 0.085
Contrast Clustering 0.508

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.748
Color Clustering 0.836
Color Transition Smoothness 0.781
Transition Uniformity 0.961
Sharp Transition Ratio 0.1
Transition Directionality 0.037
Mean Saturation 0.306
Saturation Variance 0.005
Low Saturation Ratio 0.495
Medium Saturation Ratio 0.502
High Saturation Ratio 0.003
Saturation Clustering 1.0
Hue Concentration 0.959
Complementary Balance 0.002
Analogous Dominance 0.997
Temperature Bias 0.995

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). Meditations — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0542.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/meditations_630.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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