AQC0795

Nanopublication — Computational Image Analysis - AQC0795

Claim 1: Computational Image Analysis - AQC0795

The artwork D Minor [1] - Research on Harmony - Variation 5 (AQC0795) [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]: 2971x3961 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E1A22B 23.0 yellow-orange goldenrod
2 BB7F1C 11.7 yellow-orange darkgoldenrod
3 BEA786 11.4 yellow-orange tan
4 D6A458 11.4 yellow-orange sandybrown
5 BE9147 10.4 yellow-orange peru
6 D6C4B3 9.1 orange silver
7 292B2F 7.4 gray very dark gray
8 9D6847 5.7 orange burnt sienna
9 893B2A 5.6 red-orange russet
10 414E5D 4.4 blue-violet grayish purple
11 756A35 0.3 yellow dark brown [Accent]

Color Families:

Family %
yellow-orange 67.9
orange 14.8
gray 7.4
red-orange 5.6
blue-violet 4.4
yellow 0.3

Accent Colors:

Hex Family Name Chroma
756A35 yellow dark brown 31.1

Texture Analysis

Metric Value
Global Roughness 0.172
Mean Local Roughness 0.024
Roughness Uniformity 0.021
Edge Density 0.125
Mean Gradient Magnitude 0.188
Gradient Variance 0.052
Gradient Smoothness 0.0
Directional Coherence 0.009
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.645
Spatial Variation 0.106
Texture Consistency 0.686

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.568
Brightness Variance 0.172
Brightness Uniformity 0.698
Brightness Skewness -1.039
Brightness Entropy 7.131
Rms Contrast 0.172
Michelson Contrast 1.0
Weber Contrast 0.628
Mean Local Contrast 0.026
Contrast Uniformity 0.135
Dynamic Range 1.0
Effective Dynamic Range 0.588
Shadow Percentage 13.815
Midtone Percentage 55.598
Highlight Percentage 30.587
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.013
Medium Contrast 0.032
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.188
Contrast Clustering 0.314

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.745
Color Clustering 0.54
Color Transition Smoothness 0.522
Transition Uniformity 0.639
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.572
Saturation Variance 0.062
Low Saturation Ratio 0.217
Medium Saturation Ratio 0.38
High Saturation Ratio 0.402
Saturation Clustering 0.999
Hue Concentration 0.809
Complementary Balance 0.089
Analogous Dominance 0.91
Temperature Bias 0.821

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). D Minor - Research on Harmony - Variation 5 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0795.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-minor-research-on-harmony-variation-5_8te.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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