AQC0964

Nanopublication — Computational Image Analysis - AQC0964

by Arnaud Quercy · Tritone (Eb, A) - Research on Harmony · 2026

Claim 1: Computational Image Analysis - AQC0964

The artwork Tritone [1] (Eb, A) - Research on Harmony (AQC0964) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-03-05. 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]: 1943x2915 pixels. Analysis date: 2026-03-05.

Color Analysis

Rank Color Hex % Family Name
1 CAC6BC 20.5 yellow-orange silver
2 2A5087 13.4 blue-violet grayish purple
3 3189D0 11.9 blue-violet steelblue
4 313236 11.5 gray dusty mauve
5 1B1D23 11.2 gray very dark gray
6 EAE4D5 10.1 yellow white
7 406498 8.1 blue-violet grayish purple
8 49494B 7.1 gray dusty mauve
9 6E6C6A 3.6 gray dimgray
10 979796 2.6 gray steel gray

Color Families:

Family %
gray 35.9
blue-violet 33.4
yellow-orange 20.5
yellow 10.1

Texture Analysis

Metric Value
Global Roughness 0.264
Mean Local Roughness 0.039
Roughness Uniformity 0.042
Edge Density 0.163
Mean Gradient Magnitude 0.307
Gradient Variance 0.168
Gradient Smoothness 0.0
Directional Coherence 0.005
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.674
Spatial Variation 0.19
Texture Consistency 0.583

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.464
Brightness Variance 0.264
Brightness Uniformity 0.431
Brightness Skewness 0.375
Brightness Entropy 7.589
Rms Contrast 0.264
Michelson Contrast 1.0
Weber Contrast 0.827
Mean Local Contrast 0.043
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.784
Shadow Percentage 41.39
Midtone Percentage 27.426
Highlight Percentage 31.184
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.271
Fine Contrast 0.021
Medium Contrast 0.053
Coarse Contrast 0.065
Multiscale Contrast Ratio 0.319
Edge Contrast 0.307
Contrast Clustering 0.417

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.745
Color Clustering 0.832
Color Transition Smoothness 0.183
Transition Uniformity 0.0
Sharp Transition Ratio 0.1
Transition Directionality 0.006
Mean Saturation 0.312
Saturation Variance 0.085
Low Saturation Ratio 0.597
Medium Saturation Ratio 0.23
High Saturation Ratio 0.173
Saturation Clustering 0.999
Hue Concentration 0.849
Complementary Balance 0.072
Analogous Dominance 0.926
Temperature Bias -0.845

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 (2026). Tritone (Eb, A) - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0964.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2026/03/tritone-eb-a-research-on-harmony_1yn0.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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