AQC0737

Nanopublication — Computational Image Analysis - AQC0737

Claim 1: Computational Image Analysis - AQC0737

Computational image analysis [3] of artwork F Minor [1] - Research on Harmony - Variation 11 (AQC0737) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 2026-02-04.

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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 5F95CE 17.8 blue-violet cornflowerblue
2 68355D 14.3 red-violet dusty mauve
3 593C2E 13.5 orange dark brown
4 7096BF 13.0 blue-violet cadetblue
5 E2B384 11.0 orange burlywood
6 321A1B 10.5 red-orange very dark gray
7 744A73 9.0 red-violet dusty mauve
8 DA4554 5.1 red-orange indianred
9 F05C6C 4.6 red-orange salmon
10 CA3120 1.2 red-orange firebrick
11 39234F 0.3 violet very dark purple [Accent]
12 97A7B2 0.3 blue steel gray [Accent]

Color Families:

Family %
blue-violet 30.8
orange 24.5
red-violet 23.3
red-orange 21.4
violet 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
39234F violet very dark purple 30.5
97A7B2 blue steel gray 8.5

Texture Analysis

Metric Value
Global Roughness 0.183
Mean Local Roughness 0.019
Roughness Uniformity 0.016
Edge Density 0.098
Mean Gradient Magnitude 0.152
Gradient Variance 0.029
Gradient Smoothness 0.0
Directional Coherence 0.01
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.648
Spatial Variation 0.139
Texture Consistency 0.534

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.428
Brightness Variance 0.183
Brightness Uniformity 0.572
Brightness Skewness 0.048
Brightness Entropy 7.15
Rms Contrast 0.183
Michelson Contrast 1.0
Weber Contrast 0.726
Mean Local Contrast 0.021
Contrast Uniformity 0.196
Dynamic Range 1.0
Effective Dynamic Range 0.616
Shadow Percentage 39.1
Midtone Percentage 50.194
Highlight Percentage 10.706
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.011
Medium Contrast 0.026
Coarse Contrast 0.034
Multiscale Contrast Ratio 0.31
Edge Contrast 0.152
Contrast Clustering 0.466

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.781
Color Clustering 0.48
Color Transition Smoothness 0.608
Transition Uniformity 0.813
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.498
Saturation Variance 0.012
Low Saturation Ratio 0.032
Medium Saturation Ratio 0.928
High Saturation Ratio 0.04
Saturation Clustering 0.999
Hue Concentration 0.397
Complementary Balance 0.111
Analogous Dominance 0.526
Temperature Bias 0.314

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). F Minor - Research on Harmony - Variation 11 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0737.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/f-minor-research-on-harmony-variation-11_86u.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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