AQC0680

Nanopublication — Computational Image Analysis - AQC0680

by Arnaud Quercy · Ab+ - Research on Harmony - Variation 1 · 2024

Claim 1: Computational Image Analysis - AQC0680

K-means clustering analysis [3] (10 colors) performed on artwork Ab+ - Research [1] on Harmony - Variation 1 (AQC0680) [2] by Arnaud Quercy [2] on 2026-02-04. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

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]: 2467x3701 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DADCD8 28.3 white gainsboro
2 D2C9B8 16.3 yellow-orange silver
3 92B8AA 13.4 green darkseagreen
4 3B4040 9.0 gray darkslategray
5 C6B993 8.5 yellow-orange tan
6 8B978F 7.8 yellow-green lightslategray
7 212727 5.9 gray very dark gray
8 A0B36D 5.4 yellow-green ochre
9 686E68 3.8 gray dimgray
10 915221 1.6 orange burnt sienna
11 B05E44 0.3 red-orange burnt sienna [Accent]

Color Families:

Family %
white 28.3
yellow-orange 24.8
gray 18.7
green 13.4
yellow-green 13.2
orange 1.6
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
B05E44 red-orange burnt sienna 43.1

Texture Analysis

Metric Value
Global Roughness 0.225
Mean Local Roughness 0.015
Roughness Uniformity 0.022
Edge Density 0.038
Mean Gradient Magnitude 0.134
Gradient Variance 0.081
Gradient Smoothness 0.0
Directional Coherence 0.105
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.595
Spatial Variation 0.138
Texture Consistency 0.524

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.658
Brightness Variance 0.225
Brightness Uniformity 0.658
Brightness Skewness -1.111
Brightness Entropy 7.075
Rms Contrast 0.225
Michelson Contrast 1.0
Weber Contrast 0.729
Mean Local Contrast 0.017
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.69
Shadow Percentage 15.122
Midtone Percentage 22.087
Highlight Percentage 62.791
Shadow Clipping 0.006
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.022
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.134
Contrast Clustering 0.476

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.731
Color Clustering 0.816
Color Transition Smoothness 0.645
Transition Uniformity 0.438
Sharp Transition Ratio 0.1
Transition Directionality 0.12
Mean Saturation 0.158
Saturation Variance 0.023
Low Saturation Ratio 0.85
Medium Saturation Ratio 0.135
High Saturation Ratio 0.015
Saturation Clustering 0.999
Hue Concentration 0.505
Complementary Balance 0.065
Analogous Dominance 0.524
Temperature Bias -0.194

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). Ab+ - Research on Harmony - Variation 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0680.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/ab-research-on-harmony-variation-1_7ko.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)

09b92fdd33035bfb8b3f0572c0e045b3b43d673478f2975451c8702934b62253