AQC0839

Nanopublication — Computational Image Analysis - AQC0839

by Arnaud Quercy · G Major - Research on Harmony - Variation 6 · 2025

Claim 1: Computational Image Analysis - AQC0839

K-means clustering analysis [3] (10 colors) performed on artwork G Major [1] - Research on Harmony - Variation 6 (AQC0839) [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]: 2381x3175 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CCCAC1 17.5 yellow silver
2 C6D2A7 15.9 yellow-green tan
3 B6C293 15.2 yellow-green steel gray
4 DFDCD6 12.2 white gainsboro
5 B7B6AD 12.1 yellow steel gray
6 A0A88B 10.3 yellow-green darkseagreen
7 AB6B17 5.6 orange darkgoldenrod
8 C9964B 4.6 yellow-orange peru
9 828873 3.4 yellow-green gray
10 2D2A25 3.3 gray very dark gray
11 1C0A03 0.3 red-orange black [Accent]

Color Families:

Family %
yellow-green 44.8
yellow 29.6
white 12.2
orange 5.6
yellow-orange 4.6
gray 3.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
1C0A03 red-orange black 7.8

Texture Analysis

Metric Value
Global Roughness 0.149
Mean Local Roughness 0.031
Roughness Uniformity 0.024
Edge Density 0.175
Mean Gradient Magnitude 0.243
Gradient Variance 0.07
Gradient Smoothness 0.0
Directional Coherence 0.005
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.63
Spatial Variation 0.057
Texture Consistency 0.73

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.71
Brightness Variance 0.149
Brightness Uniformity 0.79
Brightness Skewness -1.888
Brightness Entropy 6.882
Rms Contrast 0.149
Michelson Contrast 1.0
Weber Contrast 0.372
Mean Local Contrast 0.032
Contrast Uniformity 0.274
Dynamic Range 1.0
Effective Dynamic Range 0.455
Shadow Percentage 3.32
Midtone Percentage 21.43
Highlight Percentage 75.25
Shadow Clipping 0.006
Highlight Clipping 0.011
Tonal Balance 0.0
Fine Contrast 0.018
Medium Contrast 0.04
Coarse Contrast 0.06
Multiscale Contrast Ratio 0.308
Edge Contrast 0.243
Contrast Clustering 0.27

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.719
Color Clustering 0.442
Color Transition Smoothness 0.408
Transition Uniformity 0.553
Sharp Transition Ratio 0.1
Transition Directionality 0.007
Mean Saturation 0.202
Saturation Variance 0.048
Low Saturation Ratio 0.852
Medium Saturation Ratio 0.075
High Saturation Ratio 0.073
Saturation Clustering 0.999
Hue Concentration 0.926
Complementary Balance 0.003
Analogous Dominance 0.987
Temperature Bias 0.315

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 (2025). G Major - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0839.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/g-major-research-on-harmony-variation-6_9ai.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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