AQC0439

Nanopublication — Computational Image Analysis - AQC0439

by Arnaud Quercy · C# minor - Reflexions 4 · 2023

Claim 1: Computational Image Analysis - AQC0439

Analysis record [3]: C# minor - Reflexions [1] 4 (AQC0439) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-02-04.

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]: 1536x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 C5C0B5 20.6 yellow-orange silver
2 ACACA2 18.2 yellow-green steel gray
3 969687 15.1 yellow-green gray
4 DBD3C7 10.7 yellow-orange lightgray
5 6C7975 8.5 green dimgray
6 2C2822 7.1 yellow-orange very dark gray
7 48554D 6.4 yellow-green darkslategray
8 A08551 5.6 yellow-orange peru
9 77593A 4.7 orange dark brown
10 D9B37C 3.2 yellow-orange burlywood
11 F7F6EC 0.3 yellow white [Accent]
12 899CB9 0.3 blue-violet steel gray [Accent]
13 82C2D1 0.3 blue-green skyblue [Accent]
14 1A0C04 0.3 red-orange black [Accent]
15 9AB5C6 0.3 blue steel gray [Accent]

Color Families:

Family %
yellow-orange 47.2
yellow-green 39.7
green 8.5
orange 4.7
yellow 0.3
blue-violet 0.3
blue-green 0.3
red-orange 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
F7F6EC yellow white 5.1
899CB9 blue-violet steel gray 17.0
82C2D1 blue-green skyblue 22.0
1A0C04 red-orange black 7.8
9AB5C6 blue steel gray 13.4

Texture Analysis

Metric Value
Global Roughness 0.193
Mean Local Roughness 0.025
Roughness Uniformity 0.022
Edge Density 0.124
Mean Gradient Magnitude 0.199
Gradient Variance 0.063
Gradient Smoothness 0.0
Directional Coherence 0.008
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.617
Spatial Variation 0.065
Texture Consistency 0.737

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.596
Brightness Variance 0.193
Brightness Uniformity 0.677
Brightness Skewness -0.828
Brightness Entropy 7.445
Rms Contrast 0.193
Michelson Contrast 1.0
Weber Contrast 0.627
Mean Local Contrast 0.026
Contrast Uniformity 0.114
Dynamic Range 1.0
Effective Dynamic Range 0.639
Shadow Percentage 11.963
Midtone Percentage 43.106
Highlight Percentage 44.93
Shadow Clipping 0.003
Highlight Clipping 0.002
Tonal Balance 0.133
Fine Contrast 0.014
Medium Contrast 0.033
Coarse Contrast 0.049
Multiscale Contrast Ratio 0.283
Edge Contrast 0.199
Contrast Clustering 0.263

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.681
Color Clustering 0.786
Color Transition Smoothness 0.489
Transition Uniformity 0.568
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.192
Saturation Variance 0.028
Low Saturation Ratio 0.799
Medium Saturation Ratio 0.192
High Saturation Ratio 0.009
Saturation Clustering 0.999
Hue Concentration 0.602
Complementary Balance 0.134
Analogous Dominance 0.76
Temperature Bias 0.428

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 (2023). C# minor - Reflexions 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0439.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/c-minor-reflexions-4_4yy.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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