AQC0829

Nanopublication — Computational Image Analysis - AQC0829

by Arnaud Quercy · F Major - Research on Harmony - Variation 8 · 2025

Claim 1: Computational Image Analysis - AQC0829

The artwork F Major [1] - Research on Harmony - Variation 8 (AQC0829) [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]: 2262x3134 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E0DBD2 27.7 yellow-orange gainsboro
2 C8CAC4 15.7 white silver
3 E0CAAD 12.9 yellow-orange wheat
4 B7A99B 11.3 orange steel gray
5 D2B796 9.4 yellow-orange tan
6 A19184 5.9 orange rosybrown
7 2E252E 5.6 red-violet very dark gray
8 C1936D 4.1 orange ochre
9 443F50 4.0 violet dusty mauve
10 7D6F64 3.3 orange dimgray

Color Families:

Family %
yellow-orange 50.0
orange 24.6
white 15.7
red-violet 5.6
violet 4.0

Texture Analysis

Metric Value
Global Roughness 0.196
Mean Local Roughness 0.015
Roughness Uniformity 0.017
Edge Density 0.069
Mean Gradient Magnitude 0.132
Gradient Variance 0.035
Gradient Smoothness 0.0
Directional Coherence 0.032
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.607
Spatial Variation 0.096
Texture Consistency 0.428

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.708
Brightness Variance 0.196
Brightness Uniformity 0.723
Brightness Skewness -1.636
Brightness Entropy 6.965
Rms Contrast 0.196
Michelson Contrast 1.0
Weber Contrast 0.557
Mean Local Contrast 0.017
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.686
Shadow Percentage 9.379
Midtone Percentage 17.228
Highlight Percentage 73.393
Shadow Clipping 0.001
Highlight Clipping 0.033
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.021
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.132
Contrast Clustering 0.572

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.737
Color Clustering 0.877
Color Transition Smoothness 0.671
Transition Uniformity 0.778
Sharp Transition Ratio 0.1
Transition Directionality 0.04
Mean Saturation 0.161
Saturation Variance 0.013
Low Saturation Ratio 0.88
Medium Saturation Ratio 0.12
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.75
Complementary Balance 0.031
Analogous Dominance 0.833
Temperature Bias 0.818

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 (2025). F Major - Research on Harmony - Variation 8 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0829.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/f-major-research-on-harmony-variation-8_96m.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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