AQC0531

Nanopublication — Computational Image Analysis - AQC0531

Claim 1: Computational Image Analysis - AQC0531

K-means clustering analysis [3] (10 colors) performed on artwork D Major9 - Research [1] on Harmony - Variation 11 (AQC0531) [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]: 1862x2483 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E6E5E0 20.3 white white
2 B68D67 16.8 orange rosybrown
3 C19E7E 12.9 orange tan
4 A87D52 11.0 orange peru
5 D8D6D0 10.3 white lightgray
6 8C8A87 6.7 gray gray
7 D2B398 6.5 orange burlywood
8 706D6A 6.5 gray dimgray
9 4F4B4A 5.4 gray darkslategray
10 ACABA8 3.6 gray steel gray
11 342927 0.3 red-orange very dark gray [Accent]
12 826641 0.3 yellow-orange burnt sienna [Accent]

Color Families:

Family %
orange 47.3
white 30.6
gray 22.1
red-orange 0.3
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
342927 red-orange very dark gray 5.8
826641 yellow-orange burnt sienna 25.7

Texture Analysis

Metric Value
Global Roughness 0.176
Mean Local Roughness 0.026
Roughness Uniformity 0.024
Edge Density 0.14
Mean Gradient Magnitude 0.211
Gradient Variance 0.064
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.136
Pattern Repetition 1.0
Detail Frequency Ratio 0.65
Spatial Variation 0.082
Texture Consistency 0.793

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.662
Brightness Variance 0.176
Brightness Uniformity 0.735
Brightness Skewness -0.143
Brightness Entropy 7.063
Rms Contrast 0.176
Michelson Contrast 0.984
Weber Contrast 0.504
Mean Local Contrast 0.028
Contrast Uniformity 0.107
Dynamic Range 0.992
Effective Dynamic Range 0.553
Shadow Percentage 3.864
Midtone Percentage 53.258
Highlight Percentage 42.877
Shadow Clipping 0.0
Highlight Clipping 0.003
Tonal Balance 0.0
Fine Contrast 0.014
Medium Contrast 0.035
Coarse Contrast 0.051
Multiscale Contrast Ratio 0.268
Edge Contrast 0.211
Contrast Clustering 0.207

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.728
Color Clustering 0.79
Color Transition Smoothness 0.471
Transition Uniformity 0.6
Sharp Transition Ratio 0.1
Transition Directionality 0.016
Mean Saturation 0.213
Saturation Variance 0.04
Low Saturation Ratio 0.618
Medium Saturation Ratio 0.382
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.992
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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). D Major9 - Research on Harmony - Variation 11 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0531.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major9-research-on-harmony-variation-11_5yq.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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