AQC0749

Nanopublication — Computational Image Analysis - AQC0749

Claim 1: Computational Image Analysis - AQC0749

K-means clustering analysis [3] (10 colors) performed on artwork C Minor [1] - Research on Harmony - Variation 7 (AQC0749) [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]: 2964x3952 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 5A4062 21.5 red-violet dusty mauve
2 9A544B 15.1 red-orange burnt sienna
3 BC433E 15.1 red-orange burnt sienna
4 E64B3B 14.4 red-orange tomato
5 A991D6 8.1 violet mediumpurple
6 302B36 7.3 violet very dark gray
7 E8C7C8 5.6 red-orange thistle
8 C97162 5.2 red-orange indianred
9 EF8414 3.9 orange darkorange
10 77629E 3.6 violet dusty mauve
11 23050A 0.3 red very dark gray [Accent]
12 706148 0.3 yellow-orange dimgray [Accent]

Color Families:

Family %
red-orange 55.5
red-violet 21.5
violet 19.0
orange 3.9
red 0.3
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
23050A red very dark gray 13.3
706148 yellow-orange dimgray 16.1

Texture Analysis

Metric Value
Global Roughness 0.154
Mean Local Roughness 0.011
Roughness Uniformity 0.014
Edge Density 0.041
Mean Gradient Magnitude 0.114
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.021
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.584
Spatial Variation 0.081
Texture Consistency 0.36

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.434
Brightness Variance 0.154
Brightness Uniformity 0.644
Brightness Skewness 0.678
Brightness Entropy 7.134
Rms Contrast 0.154
Michelson Contrast 1.0
Weber Contrast 0.595
Mean Local Contrast 0.014
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.569
Shadow Percentage 24.38
Midtone Percentage 67.51
Highlight Percentage 8.11
Shadow Clipping 0.001
Highlight Clipping 0.002
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.018
Coarse Contrast 0.032
Multiscale Contrast Ratio 0.171
Edge Contrast 0.114
Contrast Clustering 0.64

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.753
Color Clustering 0.283
Color Transition Smoothness 0.702
Transition Uniformity 0.779
Sharp Transition Ratio 0.1
Transition Directionality 0.03
Mean Saturation 0.513
Saturation Variance 0.042
Low Saturation Ratio 0.136
Medium Saturation Ratio 0.621
High Saturation Ratio 0.243
Saturation Clustering 1.0
Hue Concentration 0.659
Complementary Balance 0.003
Analogous Dominance 0.661
Temperature Bias 0.618

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). C Minor - Research on Harmony - Variation 7 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0749.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-minor-research-on-harmony-variation-7_8bi.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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