AQC0763

Nanopublication — Computational Image Analysis - AQC0763

Claim 1: Computational Image Analysis - AQC0763

K-means clustering analysis [3] (10 colors) performed on artwork G Minor [1] - Research on Harmony - Variation 6 (AQC0763) [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]: 2888x3851 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 2E2F35 20.1 gray darkslategray
2 695388 15.3 violet dusty mauve
3 DEA465 14.1 orange sandybrown
4 B95C2C 13.7 orange burnt sienna
5 DFBB97 12.3 orange burlywood
6 CD8651 9.3 orange peru
7 4D424B 5.0 red-violet dusty mauve
8 BBB4AC 4.8 yellow-orange steel gray
9 EEA11F 3.1 yellow-orange goldenrod
10 E1D8D9 2.1 white gainsboro
11 420F07 0.3 red-orange very dark red [Accent]
12 1C0F14 0.3 red black [Accent]

Color Families:

Family %
orange 49.4
gray 20.1
violet 15.3
yellow-orange 8.0
red-violet 5.0
white 2.1
red-orange 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
420F07 red-orange very dark red 29.4
1C0F14 red black 8.1

Texture Analysis

Metric Value
Global Roughness 0.215
Mean Local Roughness 0.017
Roughness Uniformity 0.016
Edge Density 0.079
Mean Gradient Magnitude 0.16
Gradient Variance 0.045
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.113
Pattern Repetition 1.0
Detail Frequency Ratio 0.593
Spatial Variation 0.165
Texture Consistency 0.378

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.49
Brightness Variance 0.215
Brightness Uniformity 0.561
Brightness Skewness -0.086
Brightness Entropy 7.42
Rms Contrast 0.215
Michelson Contrast 1.0
Weber Contrast 0.741
Mean Local Contrast 0.02
Contrast Uniformity 0.031
Dynamic Range 1.0
Effective Dynamic Range 0.616
Shadow Percentage 26.567
Midtone Percentage 43.009
Highlight Percentage 30.424
Shadow Clipping 0.002
Highlight Clipping 0.004
Tonal Balance 0.104
Fine Contrast 0.008
Medium Contrast 0.025
Coarse Contrast 0.044
Multiscale Contrast Ratio 0.182
Edge Contrast 0.16
Contrast Clustering 0.622

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.782
Color Clustering 0.503
Color Transition Smoothness 0.587
Transition Uniformity 0.699
Sharp Transition Ratio 0.1
Transition Directionality 0.017
Mean Saturation 0.427
Saturation Variance 0.056
Low Saturation Ratio 0.331
Medium Saturation Ratio 0.521
High Saturation Ratio 0.148
Saturation Clustering 0.999
Hue Concentration 0.541
Complementary Balance 0.019
Analogous Dominance 0.703
Temperature Bias 0.606

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). G Minor - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0763.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/g-minor-research-on-harmony-variation-6_8gy.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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