AQC0552

Nanopublication — Computational Image Analysis - AQC0552

by Arnaud Quercy · C Major9 - Research on Harmony - Variation 4 · 2024

Claim 1: Computational Image Analysis - AQC0552

K-means clustering analysis [3] (10 colors) performed on artwork C Major9 - Research [1] on Harmony - Variation 4 (AQC0552) [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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D3B289 24.6 yellow-orange tan
2 38321F 14.3 yellow-orange darkslategray
3 E2C39A 13.8 yellow-orange burlywood
4 9E6E13 10.6 yellow-orange darkgoldenrod
5 C99A7B 10.4 orange rosybrown
6 BE8B2C 6.4 yellow-orange peru
7 B97665 6.1 red-orange indianred
8 414456 5.6 violet dusty mauve
9 5A503C 4.6 yellow-orange dark brown
10 DCCECC 3.6 red-orange lightgray

Color Families:

Family %
yellow-orange 74.3
orange 10.4
red-orange 9.7
violet 5.6

Texture Analysis

Metric Value
Global Roughness 0.214
Mean Local Roughness 0.019
Roughness Uniformity 0.014
Edge Density 0.115
Mean Gradient Magnitude 0.187
Gradient Variance 0.029
Gradient Smoothness 0.088
Directional Coherence 0.029
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.62
Spatial Variation 0.178
Texture Consistency 0.447

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.558
Brightness Variance 0.214
Brightness Uniformity 0.617
Brightness Skewness -0.562
Brightness Entropy 7.326
Rms Contrast 0.214
Michelson Contrast 1.0
Weber Contrast 0.729
Mean Local Contrast 0.023
Contrast Uniformity 0.334
Dynamic Range 1.0
Effective Dynamic Range 0.627
Shadow Percentage 22.407
Midtone Percentage 31.657
Highlight Percentage 45.936
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.005
Fine Contrast 0.01
Medium Contrast 0.028
Coarse Contrast 0.051
Multiscale Contrast Ratio 0.196
Edge Contrast 0.187
Contrast Clustering 0.553

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.787
Color Clustering 0.644
Color Transition Smoothness 0.525
Transition Uniformity 0.806
Sharp Transition Ratio 0.1
Transition Directionality 0.028
Mean Saturation 0.438
Saturation Variance 0.044
Low Saturation Ratio 0.185
Medium Saturation Ratio 0.647
High Saturation Ratio 0.168
Saturation Clustering 0.999
Hue Concentration 0.88
Complementary Balance 0.053
Analogous Dominance 0.946
Temperature Bias 0.894

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 Major9 - Research on Harmony - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0552.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-major9-research-on-harmony-variation-4_66w.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)

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