AQC0626

Nanopublication — Computational Image Analysis - AQC0626

by Arnaud Quercy · D minor - Research on Harmony · 2024

Claim 1: Computational Image Analysis - AQC0626

The artwork D minor - Research [1] on Harmony (AQC0626) [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]: 2333x3499 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 352136 22.4 red-violet very dark purple
2 E8AA37 17.1 yellow-orange goldenrod
3 E66020 14.6 orange chocolate
4 48384E 13.4 red-violet dusty mauve
5 EEB750 11.1 yellow-orange sandybrown
6 EE6F3E 11.0 orange tomato
7 100505 3.8 black black
8 776979 3.3 red-violet dusty mauve
9 A0471A 2.8 orange burnt sienna
10 C7BAC8 0.5 red-violet silver
11 530B02 0.3 red-orange very dark red [Accent]

Color Families:

Family %
red-violet 39.5
orange 28.5
yellow-orange 28.2
black 3.8
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
530B02 red-orange very dark red 39.2

Texture Analysis

Metric Value
Global Roughness 0.23
Mean Local Roughness 0.019
Roughness Uniformity 0.027
Edge Density 0.062
Mean Gradient Magnitude 0.16
Gradient Variance 0.07
Gradient Smoothness 0.0
Directional Coherence 0.026
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.637
Spatial Variation 0.2
Texture Consistency 0.544

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.437
Brightness Variance 0.23
Brightness Uniformity 0.473
Brightness Skewness -0.122
Brightness Entropy 7.223
Rms Contrast 0.23
Michelson Contrast 1.0
Weber Contrast 0.788
Mean Local Contrast 0.021
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.612
Shadow Percentage 40.089
Midtone Percentage 33.717
Highlight Percentage 26.195
Shadow Clipping 0.009
Highlight Clipping 0.005
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.027
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.16
Contrast Clustering 0.456

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.779
Color Clustering 0.477
Color Transition Smoothness 0.571
Transition Uniformity 0.507
Sharp Transition Ratio 0.1
Transition Directionality 0.03
Mean Saturation 0.6
Saturation Variance 0.051
Low Saturation Ratio 0.12
Medium Saturation Ratio 0.413
High Saturation Ratio 0.467
Saturation Clustering 0.998
Hue Concentration 0.674
Complementary Balance 0.001
Analogous Dominance 0.645
Temperature Bias 0.732

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). D minor - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0626.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-minor-research-on-harmony_6zo.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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