AQC0437

Nanopublication — Computational Image Analysis - AQC0437

by Arnaud Quercy · Ab Major - Reflexions 3 · 2023

Claim 1: Computational Image Analysis - AQC0437

The artwork Ab Major [1] - Reflexions 3 (AQC0437) [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]: 1536x703 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DD9365 19.6 orange darksalmon
2 E8A479 17.7 orange lightsalmon
3 C0673E 15.3 orange peru
4 D07E51 14.4 orange indianred
5 B55022 8.8 orange burnt sienna
6 E06F3A 7.2 orange chocolate
7 6B391C 6.0 orange russet
8 915537 4.4 orange burnt sienna
9 3A1A08 3.8 orange very dark orange
10 30444F 2.9 blue darkslategray
11 1B232A 0.3 blue-violet very dark gray [Accent]

Color Families:

Family %
orange 97.1
blue 2.9
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
1B232A blue-violet very dark gray 6.1

Texture Analysis

Metric Value
Global Roughness 0.154
Mean Local Roughness 0.019
Roughness Uniformity 0.015
Edge Density 0.078
Mean Gradient Magnitude 0.169
Gradient Variance 0.04
Gradient Smoothness 0.0
Directional Coherence 0.013
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.603
Spatial Variation 0.077
Texture Consistency 0.621

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.531
Brightness Variance 0.154
Brightness Uniformity 0.71
Brightness Skewness -0.893
Brightness Entropy 7.111
Rms Contrast 0.154
Michelson Contrast 0.965
Weber Contrast 0.584
Mean Local Contrast 0.021
Contrast Uniformity 0.211
Dynamic Range 0.871
Effective Dynamic Range 0.494
Shadow Percentage 12.702
Midtone Percentage 65.749
Highlight Percentage 21.549
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.026
Coarse Contrast 0.042
Multiscale Contrast Ratio 0.237
Edge Contrast 0.169
Contrast Clustering 0.379

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.733
Color Clustering 0.47
Color Transition Smoothness 0.565
Transition Uniformity 0.71
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.619
Saturation Variance 0.019
Low Saturation Ratio 0.007
Medium Saturation Ratio 0.724
High Saturation Ratio 0.269
Saturation Clustering 0.999
Hue Concentration 0.945
Complementary Balance 0.026
Analogous Dominance 0.974
Temperature Bias 0.947

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 (2023). Ab Major - Reflexions 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0437.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/ab-major-reflexions-3_4y6.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)

fe343c70e40c3e3e8926cfea9735b0d7ce03959971af7b616ef0acc9fa165bea