AQC0592

Nanopublication — Computational Image Analysis - AQC0592

Claim 1: Computational Image Analysis - AQC0592

K-means clustering analysis [3] (10 colors) performed on artwork E minor - Research [1] on Harmony (AQC0592) [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]: 2561x3415 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CA7457 21.1 orange indianred
2 E88455 20.0 orange coral
3 DD8F76 15.6 red-orange darksalmon
4 C7D3AB 12.3 yellow-green silver
5 418334 8.0 yellow-green dark brown
6 5D5F62 6.6 gray grayish purple
7 8E9187 5.5 yellow-green gray
8 161411 4.0 black black
9 EECE2A 3.7 yellow-orange gold
10 B33615 3.0 red-orange firebrick
11 B8AD8A 0.3 yellow tan [Accent]
12 32333E 0.3 violet dusty mauve [Accent]
13 E2B5B9 0.3 red lightpink [Accent]

Color Families:

Family %
orange 41.1
yellow-green 25.8
red-orange 18.6
gray 6.6
black 4.0
yellow-orange 3.7
yellow 0.3
violet 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
B8AD8A yellow tan 19.1
32333E violet dusty mauve 7.3
E2B5B9 red lightpink 17.5

Texture Analysis

Metric Value
Global Roughness 0.166
Mean Local Roughness 0.018
Roughness Uniformity 0.03
Edge Density 0.06
Mean Gradient Magnitude 0.141
Gradient Variance 0.077
Gradient Smoothness 0.0
Directional Coherence 0.096
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.65
Spatial Variation 0.064
Texture Consistency 0.504

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.569
Brightness Variance 0.166
Brightness Uniformity 0.709
Brightness Skewness -0.876
Brightness Entropy 7.062
Rms Contrast 0.166
Michelson Contrast 1.0
Weber Contrast 0.533
Mean Local Contrast 0.02
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.506
Shadow Percentage 5.98
Midtone Percentage 72.341
Highlight Percentage 21.679
Shadow Clipping 0.019
Highlight Clipping 0.017
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.025
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.141
Contrast Clustering 0.496

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.737
Color Clustering 0.342
Color Transition Smoothness 0.64
Transition Uniformity 0.505
Sharp Transition Ratio 0.1
Transition Directionality 0.099
Mean Saturation 0.491
Saturation Variance 0.042
Low Saturation Ratio 0.238
Medium Saturation Ratio 0.678
High Saturation Ratio 0.084
Saturation Clustering 0.999
Hue Concentration 0.797
Complementary Balance 0.023
Analogous Dominance 0.787
Temperature Bias 0.73

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). E minor - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0592.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/e-minor-research-on-harmony_6mg.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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