AQC0544

Nanopublication — Computational Image Analysis - AQC0544

Claim 1: Computational Image Analysis - AQC0544

Computational image analysis [3] of artwork Meditations [1] - Variation 2 (AQC0544) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 2026-02-04.

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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 777672 19.6 gray gray
2 878887 14.6 gray grey
3 8B8070 12.2 yellow-orange dimgray
4 A29480 11.7 yellow-orange rosybrown
5 B7A993 10.9 yellow-orange steel gray
6 9B9E9D 10.6 gray steel gray
7 686662 10.1 gray dimgrey
8 C6BBA8 7.5 yellow-orange silver
9 6A312A 2.2 red-orange russet
10 1E0905 0.5 red-orange black
11 F3D8BE 0.3 orange wheat [Accent]
12 414E51 0.3 blue darkslategray [Accent]

Color Families:

Family %
gray 54.9
yellow-orange 42.4
red-orange 2.7
orange 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
F3D8BE orange wheat 16.8
414E51 blue darkslategray 5.7

Texture Analysis

Metric Value
Global Roughness 0.111
Mean Local Roughness 0.014
Roughness Uniformity 0.011
Edge Density 0.064
Mean Gradient Magnitude 0.141
Gradient Variance 0.019
Gradient Smoothness 0.01
Directional Coherence 0.009
Pattern Complexity 0.112
Pattern Repetition 1.0
Detail Frequency Ratio 0.596
Spatial Variation 0.072
Texture Consistency 0.721

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.542
Brightness Variance 0.111
Brightness Uniformity 0.795
Brightness Skewness -0.367
Brightness Entropy 6.775
Rms Contrast 0.111
Michelson Contrast 1.0
Weber Contrast 0.392
Mean Local Contrast 0.016
Contrast Uniformity 0.271
Dynamic Range 1.0
Effective Dynamic Range 0.333
Shadow Percentage 2.736
Midtone Percentage 82.581
Highlight Percentage 14.683
Shadow Clipping 0.0
Highlight Clipping 0.002
Tonal Balance 0.0
Fine Contrast 0.007
Medium Contrast 0.021
Coarse Contrast 0.037
Multiscale Contrast Ratio 0.186
Edge Contrast 0.141
Contrast Clustering 0.279

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.709
Color Clustering 0.676
Color Transition Smoothness 0.642
Transition Uniformity 0.878
Sharp Transition Ratio 0.1
Transition Directionality 0.008
Mean Saturation 0.134
Saturation Variance 0.015
Low Saturation Ratio 0.953
Medium Saturation Ratio 0.039
High Saturation Ratio 0.008
Saturation Clustering 1.0
Hue Concentration 0.982
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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). Meditations - Variation 2 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0544.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/meditations-variation-2_63s.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)

6f187d1143b045c564b202a8920698fffc9161eab907360367b058b983abee95