AQC0792

Nanopublication — Computational Image Analysis - AQC0792

by Arnaud Quercy · C Octaves - Reflexions 26 · 2024

Claim 1: Computational Image Analysis - AQC0792

K-means clustering analysis [3] (10 colors) performed on artwork C Octaves [1] - Reflexions 26 (AQC0792) [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]: 2424x3636 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D9B8D3 13.7 red-violet thistle
2 6E2824 13.3 red-orange russet
3 C39EB9 12.7 red-violet steel gray
4 D3ADC6 12.2 red-violet silver
5 B794A8 10.9 red-violet steel gray
6 131220 10.0 violet very dark gray
7 C23130 9.8 red-orange firebrick
8 CD9FAC 8.5 red rosybrown
9 242632 8.3 blue-violet very dark gray
10 7C5157 0.6 red dimgray

Color Families:

Family %
red-violet 49.5
red-orange 23.1
violet 10.0
red 9.0
blue-violet 8.3

Texture Analysis

Metric Value
Global Roughness 0.255
Mean Local Roughness 0.007
Roughness Uniformity 0.017
Edge Density 0.012
Mean Gradient Magnitude 0.064
Gradient Variance 0.04
Gradient Smoothness 0.0
Directional Coherence 0.105
Pattern Complexity 0.108
Pattern Repetition 1.0
Detail Frequency Ratio 0.588
Spatial Variation 0.181
Texture Consistency 0.463

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.5
Brightness Variance 0.255
Brightness Uniformity 0.49
Brightness Skewness -0.455
Brightness Entropy 6.874
Rms Contrast 0.255
Michelson Contrast 1.0
Weber Contrast 0.846
Mean Local Contrast 0.009
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.694
Shadow Percentage 31.968
Midtone Percentage 24.557
Highlight Percentage 43.476
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.004
Medium Contrast 0.011
Coarse Contrast 0.02
Multiscale Contrast Ratio 0.191
Edge Contrast 0.064
Contrast Clustering 0.537

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.749
Color Clustering 0.828
Color Transition Smoothness 0.821
Transition Uniformity 0.722
Sharp Transition Ratio 0.1
Transition Directionality 0.136
Mean Saturation 0.346
Saturation Variance 0.053
Low Saturation Ratio 0.628
Medium Saturation Ratio 0.234
High Saturation Ratio 0.137
Saturation Clustering 0.999
Hue Concentration 0.658
Complementary Balance 0.001
Analogous Dominance 0.756
Temperature Bias 0.553

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 Octaves - Reflexions 26 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0792.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-octaves-reflexions-26_8s8.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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