AQC0701

Nanopublication — Computational Image Analysis - AQC0701

Claim 1: Computational Image Analysis - AQC0701

K-means clustering analysis [3] (10 colors) performed on artwork Db Major [1] - Research on Harmony - Variation 3 (AQC0701) [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]: 2840x3550 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DFC293 21.4 yellow-orange burlywood
2 2C2A3B 17.8 violet very dark gray
3 674451 14.2 red dusty mauve
4 85A79F 11.7 green darkseagreen
5 334779 10.3 blue-violet grayish purple
6 4B403A 6.7 orange darkslategray
7 7C8D7F 5.8 yellow-green gray
8 5A99AE 4.6 blue cadetblue
9 AE6478 4.3 red indianred
10 C3A579 3.3 yellow-orange ochre
11 2E1003 0.3 red-orange very dark red [Accent]
12 447C89 0.3 blue-green steelblue [Accent]
13 D8D5C8 0.3 yellow lightgray [Accent]
14 755979 0.3 red-violet dusty mauve [Accent]

Color Families:

Family %
yellow-orange 24.7
red 18.5
violet 17.8
green 11.7
blue-violet 10.3
orange 6.7
yellow-green 5.8
blue 4.6
red-orange 0.3
blue-green 0.3
yellow 0.3
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
2E1003 red-orange very dark red 18.4
447C89 blue-green steelblue 19.8
D8D5C8 yellow lightgray 7.1
755979 red-violet dusty mauve 22.8

Texture Analysis

Metric Value
Global Roughness 0.224
Mean Local Roughness 0.006
Roughness Uniformity 0.013
Edge Density 0.006
Mean Gradient Magnitude 0.042
Gradient Variance 0.017
Gradient Smoothness 0.0
Directional Coherence 0.243
Pattern Complexity 0.102
Pattern Repetition 1.0
Detail Frequency Ratio 0.62
Spatial Variation 0.148
Texture Consistency 0.503

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.459
Brightness Variance 0.224
Brightness Uniformity 0.512
Brightness Skewness 0.201
Brightness Entropy 7.027
Rms Contrast 0.224
Michelson Contrast 1.0
Weber Contrast 0.768
Mean Local Contrast 0.006
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.639
Shadow Percentage 45.747
Midtone Percentage 30.802
Highlight Percentage 23.45
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.003
Medium Contrast 0.008
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.042
Contrast Clustering 0.497

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.755
Color Clustering 0.801
Color Transition Smoothness 0.88
Transition Uniformity 0.885
Sharp Transition Ratio 0.1
Transition Directionality 0.264
Mean Saturation 0.337
Saturation Variance 0.017
Low Saturation Ratio 0.353
Medium Saturation Ratio 0.646
High Saturation Ratio 0.001
Saturation Clustering 1.0
Hue Concentration 0.206
Complementary Balance 0.089
Analogous Dominance 0.573
Temperature Bias 0.239

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). Db Major - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0701.html

[2] Quercy, A. (2024). Db Major - Research on Harmony - Variation 3 - Gallery. https://artquamanima.com/en/artworks/2024/01/db-major-research-on-harmony-variation-3_7su.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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