AQC0514

Nanopublication — Computational Image Analysis - AQC0514

by Arnaud Quercy · Archimedes, the owl · 2024

Claim 1: Computational Image Analysis - AQC0514

The artwork Archimedes [1], the owl (AQC0514) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2025-12-17. 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]: 1638x2048 pixels. Analysis date: 2025-12-17.

Color Analysis

Rank Color Hex % Family Name
1 D7DBC9 25.7 yellow-green lightgray
2 CDCFBC 22.3 yellow-green silver
3 E2E6D6 11.3 yellow-green white
4 0E0E0F 11.0 black black
5 322B1D 9.9 yellow-orange very dark gray
6 4F442D 6.4 yellow-orange dark brown
7 66665E 3.8 yellow-green dimgray
8 736039 3.8 yellow-orange dark brown
9 93875B 3.3 yellow-orange gray
10 ACA877 2.6 yellow ochre

Color Families:

Family %
yellow-green 63.1
yellow-orange 23.3
black 11.0
yellow 2.6

Texture Analysis

Metric Value
Global Roughness 0.31
Mean Local Roughness 0.016
Roughness Uniformity 0.018
Edge Density 0.066
Mean Gradient Magnitude 0.113
Gradient Variance 0.028
Gradient Smoothness 0.0
Directional Coherence 0.165
Pattern Complexity 0.143
Pattern Repetition 1.0
Detail Frequency Ratio 0.634
Spatial Variation 0.236
Texture Consistency 0.332

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.602
Brightness Variance 0.31
Brightness Uniformity 0.485
Brightness Skewness -0.681
Brightness Entropy 6.936
Rms Contrast 0.31
Michelson Contrast 1.0
Weber Contrast 0.906
Mean Local Contrast 0.015
Contrast Uniformity 0.0
Dynamic Range 0.996
Effective Dynamic Range 0.843
Shadow Percentage 27.691
Midtone Percentage 12.215
Highlight Percentage 60.094
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.009
Medium Contrast 0.019
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.113
Contrast Clustering 0.668

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.744
Color Clustering 0.948
Color Transition Smoothness 0.713
Transition Uniformity 0.816
Sharp Transition Ratio 0.1
Transition Directionality 0.167
Mean Saturation 0.173
Saturation Variance 0.027
Low Saturation Ratio 0.791
Medium Saturation Ratio 0.205
High Saturation Ratio 0.004
Saturation Clustering 0.999
Hue Concentration 0.914
Complementary Balance 0.014
Analogous Dominance 0.96
Temperature Bias 0.874

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). Archimedes, the owl — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0514.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/archimedes-the-owl_5s4.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/11/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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