AQC0669

Nanopublication — Computational Image Analysis - AQC0669

by Arnaud Quercy · Tritone (D, G#) - Reflexions 10 · 2024

Claim 1: Computational Image Analysis - AQC0669

The artwork Tritone [1] (D, G#) - Reflexions 10 (AQC0669) [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]: 2268x3402 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CFD0CD 27.7 white lightgray
2 C3C8C7 19.2 white silver
3 D9D9D6 15.6 white gainsboro
4 8E9DA5 11.1 blue steel gray
5 9EABB0 9.9 blue steel gray
6 B5BCBD 7.6 gray steel gray
7 7E8D95 5.4 blue lightslategray
8 6E6E70 1.6 gray grayish purple
9 373535 1.2 gray darkslategray
10 B0744D 0.7 orange peru

Color Families:

Family %
white 62.6
blue 26.4
gray 10.3
orange 0.7

Texture Analysis

Metric Value
Global Roughness 0.119
Mean Local Roughness 0.01
Roughness Uniformity 0.012
Edge Density 0.023
Mean Gradient Magnitude 0.096
Gradient Variance 0.023
Gradient Smoothness 0.0
Directional Coherence 0.024
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.598
Spatial Variation 0.086
Texture Consistency 0.408

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.74
Brightness Variance 0.119
Brightness Uniformity 0.839
Brightness Skewness -1.658
Brightness Entropy 6.386
Rms Contrast 0.119
Michelson Contrast 1.0
Weber Contrast 0.312
Mean Local Contrast 0.012
Contrast Uniformity 0.0
Dynamic Range 0.996
Effective Dynamic Range 0.325
Shadow Percentage 1.193
Midtone Percentage 24.713
Highlight Percentage 74.094
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.015
Coarse Contrast 0.027
Multiscale Contrast Ratio 0.205
Edge Contrast 0.096
Contrast Clustering 0.592

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.74
Color Clustering 0.59
Color Transition Smoothness 0.76
Transition Uniformity 0.85
Sharp Transition Ratio 0.1
Transition Directionality 0.029
Mean Saturation 0.068
Saturation Variance 0.005
Low Saturation Ratio 0.99
Medium Saturation Ratio 0.01
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.412
Complementary Balance 0.272
Analogous Dominance 0.705
Temperature Bias -0.411

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). Tritone (D, G#) - Reflexions 10 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0669.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/tritone-d-g-reflexions-10_7ge.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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