AQC0671

Nanopublication — Computational Image Analysis - AQC0671

by Arnaud Quercy · C+ - Research on Harmony - Variation 3 · 2024

Claim 1: Computational Image Analysis - AQC0671

The artwork C+ - Research [1] on Harmony - Variation 3 (AQC0671) [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]: 2440x3660 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 BEA096 16.6 orange rosybrown
2 C4B5B8 16.5 red silver
3 B79588 15.3 orange steel gray
4 BAA7AA 13.5 red steel gray
5 C9ADA4 12.7 red-orange tan
6 C4BFCA 9.8 violet thistle
7 B08877 7.8 orange gray
8 C2CDE0 6.0 blue-violet lightsteelblue
9 2D2225 1.0 red very dark gray
10 565661 0.8 violet dusty mauve
11 B68C42 0.3 yellow-orange peru [Accent]

Color Families:

Family %
orange 39.7
red 30.9
red-orange 12.7
violet 10.6
blue-violet 6.0
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
B68C42 yellow-orange peru 45.7

Texture Analysis

Metric Value
Global Roughness 0.087
Mean Local Roughness 0.01
Roughness Uniformity 0.012
Edge Density 0.008
Mean Gradient Magnitude 0.086
Gradient Variance 0.018
Gradient Smoothness 0.0
Directional Coherence 0.034
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.613
Spatial Variation 0.054
Texture Consistency 0.493

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.679
Brightness Variance 0.087
Brightness Uniformity 0.872
Brightness Skewness -2.699
Brightness Entropy 6.148
Rms Contrast 0.087
Michelson Contrast 1.0
Weber Contrast 0.215
Mean Local Contrast 0.011
Contrast Uniformity 0.0
Dynamic Range 0.929
Effective Dynamic Range 0.212
Shadow Percentage 1.313
Midtone Percentage 35.62
Highlight Percentage 63.067
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.014
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.086
Contrast Clustering 0.507

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.752
Color Clustering 0.526
Color Transition Smoothness 0.78
Transition Uniformity 0.875
Sharp Transition Ratio 0.1
Transition Directionality 0.039
Mean Saturation 0.172
Saturation Variance 0.009
Low Saturation Ratio 0.907
Medium Saturation Ratio 0.091
High Saturation Ratio 0.002
Saturation Clustering 1.0
Hue Concentration 0.94
Complementary Balance 0.024
Analogous Dominance 0.97
Temperature Bias 0.943

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). C+ - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0671.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-research-on-harmony-variation-3_7h6.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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