AQC0695

Nanopublication — Computational Image Analysis - AQC0695

by Arnaud Quercy · Bb minor - Research on Harmony - Variation 3 · 2024

Claim 1: Computational Image Analysis - AQC0695

K-means clustering analysis [3] (10 colors) performed on artwork Bb minor - Research [1] on Harmony - Variation 3 (AQC0695) [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]: 2766x3458 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 2E221D 17.5 orange very dark gray
2 71A6A6 14.7 blue-green cadetblue
3 E0BB8B 14.0 yellow-orange burlywood
4 584546 13.8 red darkslategray
5 3F3227 12.1 orange darkslategrey
6 678E93 11.2 blue-green blue gray
7 8B716F 5.8 red-orange gray
8 C1A58A 4.6 orange tan
9 C99F6F 4.2 orange ochre
10 89584F 2.1 red-orange burnt sienna

Color Families:

Family %
orange 38.4
blue-green 25.9
yellow-orange 14.0
red 13.8
red-orange 7.9

Texture Analysis

Metric Value
Global Roughness 0.218
Mean Local Roughness 0.005
Roughness Uniformity 0.011
Edge Density 0.005
Mean Gradient Magnitude 0.041
Gradient Variance 0.012
Gradient Smoothness 0.0
Directional Coherence 0.2
Pattern Complexity 0.107
Pattern Repetition 1.0
Detail Frequency Ratio 0.606
Spatial Variation 0.14
Texture Consistency 0.611

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.437
Brightness Variance 0.218
Brightness Uniformity 0.501
Brightness Skewness 0.026
Brightness Entropy 7.206
Rms Contrast 0.218
Michelson Contrast 1.0
Weber Contrast 0.794
Mean Local Contrast 0.006
Contrast Uniformity 0.0
Dynamic Range 0.988
Effective Dynamic Range 0.627
Shadow Percentage 42.12
Midtone Percentage 39.43
Highlight Percentage 18.45
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.003
Medium Contrast 0.008
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.041
Contrast Clustering 0.389

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.722
Color Clustering 0.85
Color Transition Smoothness 0.882
Transition Uniformity 0.915
Sharp Transition Ratio 0.1
Transition Directionality 0.229
Mean Saturation 0.33
Saturation Variance 0.013
Low Saturation Ratio 0.449
Medium Saturation Ratio 0.547
High Saturation Ratio 0.004
Saturation Clustering 1.0
Hue Concentration 0.429
Complementary Balance 0.207
Analogous Dominance 0.714
Temperature Bias 0.43

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). Bb minor - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0695.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/bb-minor-research-on-harmony-variation-3_7qi.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/10/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)

a9581aba82a11e1049e9037f0cf7a37e11107e914dd47bfafab0a0559f9fbf7e