AQC0688

Nanopublication — Computational Image Analysis - AQC0688

by Arnaud Quercy · Tritone (C, F#) - Reflexions 22 · 2024

Claim 1: Computational Image Analysis - AQC0688

The artwork Tritone [1] (C, F#) - Reflexions 22 (AQC0688) [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]: 1920x2560 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D0CDCD 18.7 white lightgray
2 AAB1A7 15.6 yellow-green steel gray
3 C2C5C4 14.6 white silver
4 D9D7DA 13.8 white gainsboro
5 B3BCB6 11.9 gray steel gray
6 C2BAAE 9.7 yellow-orange steel gray
7 9AA89D 9.5 yellow-green steel gray
8 899688 2.7 yellow-green gray
9 303333 2.5 gray darkslategray
10 636262 1.2 gray dimgray

Color Families:

Family %
white 47.0
yellow-green 27.7
gray 15.6
yellow-orange 9.7

Texture Analysis

Metric Value
Global Roughness 0.119
Mean Local Roughness 0.012
Roughness Uniformity 0.017
Edge Density 0.025
Mean Gradient Magnitude 0.1
Gradient Variance 0.034
Gradient Smoothness 0.0
Directional Coherence 0.035
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.607
Spatial Variation 0.065
Texture Consistency 0.37

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.73
Brightness Variance 0.119
Brightness Uniformity 0.838
Brightness Skewness -2.566
Brightness Entropy 6.39
Rms Contrast 0.119
Michelson Contrast 0.992
Weber Contrast 0.243
Mean Local Contrast 0.013
Contrast Uniformity 0.0
Dynamic Range 0.984
Effective Dynamic Range 0.278
Shadow Percentage 2.744
Midtone Percentage 13.794
Highlight Percentage 83.462
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.016
Coarse Contrast 0.027
Multiscale Contrast Ratio 0.232
Edge Contrast 0.1
Contrast Clustering 0.63

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.731
Color Clustering 0.911
Color Transition Smoothness 0.751
Transition Uniformity 0.768
Sharp Transition Ratio 0.1
Transition Directionality 0.046
Mean Saturation 0.066
Saturation Variance 0.002
Low Saturation Ratio 0.994
Medium Saturation Ratio 0.006
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.592
Complementary Balance 0.03
Analogous Dominance 0.688
Temperature Bias -0.055

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 (C, F#) - Reflexions 22 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0688.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/tritone-c-f-reflexions-22_7ns.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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