AQC0613

Nanopublication — Computational Image Analysis - AQC0613

Claim 1: Computational Image Analysis - AQC0613

K-means clustering analysis [3] (10 colors) performed on artwork Bb minor - Research [1] on Harmony - Variation 1 (AQC0613) [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]: 2636x3515 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 6C2F46 27.3 red dusty mauve
2 60DCD8 23.9 green mediumturquoise
3 58C2C2 16.1 blue-green mediumaquamarine
4 7F4760 11.7 red dusty mauve
5 CDBFBA 5.0 orange silver
6 997288 4.6 red-violet dusty mauve
7 4B2C62 4.0 violet dusty mauve
8 8BEBEA 3.6 blue-green skyblue
9 2E1832 1.9 red-violet very dark purple
10 E8E1E0 1.9 white gainsboro
11 06121A 0.3 blue black [Accent]
12 060D17 0.3 blue-violet black [Accent]

Color Families:

Family %
red 39.1
green 23.9
blue-green 19.7
red-violet 6.4
orange 5.0
violet 4.0
white 1.9
blue 0.3
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
06121A blue black 7.3
060D17 blue-violet black 6.0

Texture Analysis

Metric Value
Global Roughness 0.221
Mean Local Roughness 0.031
Roughness Uniformity 0.038
Edge Density 0.128
Mean Gradient Magnitude 0.236
Gradient Variance 0.124
Gradient Smoothness 0.0
Directional Coherence 0.031
Pattern Complexity 0.127
Pattern Repetition 1.0
Detail Frequency Ratio 0.661
Spatial Variation 0.182
Texture Consistency 0.391

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.509
Brightness Variance 0.221
Brightness Uniformity 0.566
Brightness Skewness -0.046
Brightness Entropy 7.182
Rms Contrast 0.221
Michelson Contrast 1.0
Weber Contrast 0.675
Mean Local Contrast 0.032
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.576
Shadow Percentage 36.394
Midtone Percentage 26.279
Highlight Percentage 37.328
Shadow Clipping 0.003
Highlight Clipping 0.018
Tonal Balance 0.0
Fine Contrast 0.018
Medium Contrast 0.04
Coarse Contrast 0.06
Multiscale Contrast Ratio 0.305
Edge Contrast 0.236
Contrast Clustering 0.609

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.754
Color Clustering 0.69
Color Transition Smoothness 0.403
Transition Uniformity 0.209
Sharp Transition Ratio 0.1
Transition Directionality 0.043
Mean Saturation 0.498
Saturation Variance 0.021
Low Saturation Ratio 0.11
Medium Saturation Ratio 0.879
High Saturation Ratio 0.011
Saturation Clustering 0.999
Hue Concentration 0.238
Complementary Balance 0.004
Analogous Dominance 0.482
Temperature Bias -0.018

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 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0613.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/bb-minor-research-on-harmony-variation-1_6um.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)

9ca45ef3123701f275b73e026bed6bbb0116d45b62c6d573c5eb24aba5330407