AQC0632

Nanopublication — Computational Image Analysis - AQC0632

Claim 1: Computational Image Analysis - AQC0632

The artwork Eb minor - Research [1] on Harmony - Variation 4 (AQC0632) [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]: 2183x3275 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 544F62 18.5 violet dusty mauve
2 77BD5E 17.2 yellow-green darkseagreen
3 15130F 11.8 black black
4 403C4E 11.6 violet dusty mauve
5 495690 10.1 violet dusty mauve
6 61A449 8.5 yellow-green olivedrab
7 706987 6.6 violet dusty mauve
8 90D576 6.2 yellow-green lightgreen
9 E0E0D4 5.8 yellow gainsboro
10 9D9CA2 3.6 gray steel gray
11 8F5FA4 0.3 red-violet lightslategray [Accent]

Color Families:

Family %
violet 46.8
yellow-green 31.9
black 11.8
yellow 5.8
gray 3.6
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
8F5FA4 red-violet lightslategray 43.9

Texture Analysis

Metric Value
Global Roughness 0.219
Mean Local Roughness 0.032
Roughness Uniformity 0.032
Edge Density 0.163
Mean Gradient Magnitude 0.261
Gradient Variance 0.113
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.125
Pattern Repetition 1.0
Detail Frequency Ratio 0.637
Spatial Variation 0.136
Texture Consistency 0.703

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.432
Brightness Variance 0.219
Brightness Uniformity 0.492
Brightness Skewness 0.194
Brightness Entropy 7.519
Rms Contrast 0.219
Michelson Contrast 1.0
Weber Contrast 0.836
Mean Local Contrast 0.035
Contrast Uniformity 0.108
Dynamic Range 1.0
Effective Dynamic Range 0.773
Shadow Percentage 37.846
Midtone Percentage 48.849
Highlight Percentage 13.305
Shadow Clipping 0.077
Highlight Clipping 0.032
Tonal Balance 0.138
Fine Contrast 0.018
Medium Contrast 0.045
Coarse Contrast 0.07
Multiscale Contrast Ratio 0.254
Edge Contrast 0.261
Contrast Clustering 0.297

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.726
Color Clustering 0.763
Color Transition Smoothness 0.324
Transition Uniformity 0.259
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.353
Saturation Variance 0.032
Low Saturation Ratio 0.423
Medium Saturation Ratio 0.563
High Saturation Ratio 0.014
Saturation Clustering 0.997
Hue Concentration 0.23
Complementary Balance 0.066
Analogous Dominance 0.458
Temperature Bias -0.061

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). Eb minor - Research on Harmony - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0632.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/eb-minor-research-on-harmony-variation-4_720.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)

34b08f6e308f41e794fae1793dcf54696fec546b64a0cf6ea57a9179a0842026