AQC0634

Nanopublication — Computational Image Analysis - AQC0634

Claim 1: Computational Image Analysis - AQC0634

The artwork E minor - Research [1] on Harmony - Variation 1 (AQC0634) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-02-04. Method: k-means clustering with 10 colors extracted. Metrics documented: color distribution, texture analysis, brightness/contrast, spatial patterns.

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]: 2275x3412 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 ECCE2E 20.6 yellow-orange goldenrod
2 80A840 18.8 yellow-green olivedrab
3 DFB924 15.3 yellow-orange orange
4 E25D1B 11.3 orange chocolate
5 92B25D 9.8 yellow-green ochre
6 120E0A 9.0 black black
7 3F381D 5.1 yellow-orange darkslategray
8 615F42 4.4 yellow dark brown
9 CFCDB4 3.3 yellow silver
10 9E4117 2.4 orange russet
11 550B03 0.3 red-orange very dark red [Accent]

Color Families:

Family %
yellow-orange 41.0
yellow-green 28.6
orange 13.7
black 9.0
yellow 7.6
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
550B03 red-orange very dark red 40.8

Texture Analysis

Metric Value
Global Roughness 0.221
Mean Local Roughness 0.023
Roughness Uniformity 0.034
Edge Density 0.072
Mean Gradient Magnitude 0.188
Gradient Variance 0.113
Gradient Smoothness 0.0
Directional Coherence 0.019
Pattern Complexity 0.11
Pattern Repetition 1.0
Detail Frequency Ratio 0.632
Spatial Variation 0.136
Texture Consistency 0.579

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.559
Brightness Variance 0.221
Brightness Uniformity 0.605
Brightness Skewness -1.018
Brightness Entropy 7.317
Rms Contrast 0.221
Michelson Contrast 1.0
Weber Contrast 0.789
Mean Local Contrast 0.025
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.741
Shadow Percentage 16.354
Midtone Percentage 44.424
Highlight Percentage 39.222
Shadow Clipping 0.084
Highlight Clipping 0.018
Tonal Balance 0.0
Fine Contrast 0.012
Medium Contrast 0.032
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.188
Contrast Clustering 0.421

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.75
Color Clustering 0.566
Color Transition Smoothness 0.513
Transition Uniformity 0.223
Sharp Transition Ratio 0.1
Transition Directionality 0.022
Mean Saturation 0.663
Saturation Variance 0.053
Low Saturation Ratio 0.093
Medium Saturation Ratio 0.384
High Saturation Ratio 0.523
Saturation Clustering 0.997
Hue Concentration 0.913
Complementary Balance 0.003
Analogous Dominance 0.98
Temperature Bias 0.67

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 - Variation 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0634.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/e-minor-research-on-harmony-variation-1_72s.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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