AQC0486

Nanopublication — Computational Image Analysis - AQC0486

by Arnaud Quercy · Metaboles · 2023

Claim 1: Computational Image Analysis - AQC0486

K-means clustering analysis [3] (10 colors) performed on artwork Metaboles [1] (AQC0486) [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 E599A6 13.9 red tan
2 753143 13.9 red brown
3 611E31 13.7 red russet
4 D38794 13.4 red palevioletred
5 894457 10.8 red burnt sienna
6 480C1C 8.6 red very dark red
7 BE7581 8.5 red rosybrown
8 F3AFBD 8.0 red lightpink
9 9D5E6D 7.0 red gray
10 B7191D 2.2 red-orange firebrick
11 C7C343 0.3 yellow ochre [Accent]
12 28052C 0.3 red-violet very dark purple [Accent]
13 CB8D3F 0.3 orange peru [Accent]

Color Families:

Family %
red 97.8
red-orange 2.2
yellow 0.3
red-violet 0.3
orange 0.3

Accent Colors:

Hex Family Name Chroma
C7C343 yellow ochre 63.6
28052C red-violet very dark purple 29.4
CB8D3F orange peru 52.5

Texture Analysis

Metric Value
Global Roughness 0.217
Mean Local Roughness 0.076
Roughness Uniformity 0.032
Edge Density 0.371
Mean Gradient Magnitude 0.502
Gradient Variance 0.124
Gradient Smoothness 0.297
Directional Coherence 0.014
Pattern Complexity 0.105
Pattern Repetition 1.0
Detail Frequency Ratio 0.713
Spatial Variation 0.159
Texture Consistency 0.655

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.445
Brightness Variance 0.217
Brightness Uniformity 0.512
Brightness Skewness 0.067
Brightness Entropy 7.555
Rms Contrast 0.217
Michelson Contrast 1.0
Weber Contrast 0.769
Mean Local Contrast 0.073
Contrast Uniformity 0.607
Dynamic Range 1.0
Effective Dynamic Range 0.643
Shadow Percentage 39.152
Midtone Percentage 39.02
Highlight Percentage 21.828
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.299
Fine Contrast 0.045
Medium Contrast 0.087
Coarse Contrast 0.088
Multiscale Contrast Ratio 0.506
Edge Contrast 0.502
Contrast Clustering 0.345

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.717
Color Clustering 0.596
Color Transition Smoothness 0.0
Transition Uniformity 0.194
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.498
Saturation Variance 0.04
Low Saturation Ratio 0.108
Medium Saturation Ratio 0.709
High Saturation Ratio 0.183
Saturation Clustering 0.993
Hue Concentration 0.993
Complementary Balance 0.0
Analogous Dominance 0.997
Temperature Bias 0.998

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). Metaboles — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0486.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/metaboles_5h8.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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