AQC0717

Nanopublication — Computational Image Analysis - AQC0717

Claim 1: Computational Image Analysis - AQC0717

The artwork Bb Minor [1] - Research on Harmony - Variation 8 (AQC0717) [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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 9E2842 19.0 red-orange brown
2 F0A4B7 15.1 red lightpink
3 542B25 11.2 red-orange russet
4 421B15 10.6 red-orange very dark red
5 D7476B 9.4 red indianred
6 C16776 8.2 red palevioletred
7 A75169 8.0 red burnt sienna
8 6C3636 7.9 red-orange russet
9 EC5F83 6.9 red lightcoral
10 7EADBC 3.6 blue mediumaquamarine
11 EEBA92 0.3 orange burlywood [Accent]
12 1B162C 0.3 violet very dark purple [Accent]
13 9BBBB9 0.3 blue-green steel gray [Accent]
14 A6C6C2 0.3 green silver [Accent]

Color Families:

Family %
red-orange 48.7
red 47.7
blue 3.6
orange 0.3
violet 0.3
blue-green 0.3
green 0.3

Accent Colors:

Hex Family Name Chroma
EEBA92 orange burlywood 30.9
1B162C violet very dark purple 16.1
9BBBB9 blue-green steel gray 11.4
A6C6C2 green silver 12.2

Texture Analysis

Metric Value
Global Roughness 0.192
Mean Local Roughness 0.017
Roughness Uniformity 0.018
Edge Density 0.072
Mean Gradient Magnitude 0.138
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.647
Spatial Variation 0.159
Texture Consistency 0.504

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.415
Brightness Variance 0.192
Brightness Uniformity 0.537
Brightness Skewness 0.395
Brightness Entropy 7.283
Rms Contrast 0.192
Michelson Contrast 1.0
Weber Contrast 0.754
Mean Local Contrast 0.019
Contrast Uniformity 0.013
Dynamic Range 0.996
Effective Dynamic Range 0.604
Shadow Percentage 43.37
Midtone Percentage 40.365
Highlight Percentage 16.265
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.071
Fine Contrast 0.009
Medium Contrast 0.023
Coarse Contrast 0.033
Multiscale Contrast Ratio 0.267
Edge Contrast 0.138
Contrast Clustering 0.496

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.797
Color Clustering 0.577
Color Transition Smoothness 0.662
Transition Uniformity 0.808
Sharp Transition Ratio 0.1
Transition Directionality 0.023
Mean Saturation 0.566
Saturation Variance 0.025
Low Saturation Ratio 0.037
Medium Saturation Ratio 0.709
High Saturation Ratio 0.254
Saturation Clustering 0.999
Hue Concentration 0.925
Complementary Balance 0.015
Analogous Dominance 0.969
Temperature Bias 0.939

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). Bb Minor - Research on Harmony - Variation 8 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0717.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/bb-minor-research-on-harmony-variation-8_7z2.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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