AQC0843

Nanopublication — Computational Image Analysis - AQC0843

Claim 1: Computational Image Analysis - AQC0843

The artwork A minor - Research [1] on Harmony - Variation 8 (AQC0843) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-02-03. 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]: 2457x3276 pixels. Analysis date: 2026-02-03.

Color Analysis

Rank Color Hex % Family Name
1 CED1D2 19.6 white lightgray
2 CBBCE2 17.7 violet thistle
3 C7B0C8 16.1 red-violet silver
4 CFC8B7 15.0 yellow-orange lightgrey
5 CABD9E 10.9 yellow-orange tan
6 BFA0AE 6.7 red steel gray
7 A47161 5.1 red-orange indianred
8 B48F7F 4.4 orange rosybrown
9 2B2932 3.1 violet very dark gray
10 4A4854 1.5 violet dusty mauve
11 D3E1F8 0.3 blue-violet lavender [Accent]

Color Families:

Family %
yellow-orange 25.9
violet 22.3
white 19.6
red-violet 16.1
red 6.7
red-orange 5.1
orange 4.4
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
D3E1F8 blue-violet lavender 13.0

Texture Analysis

Metric Value
Global Roughness 0.139
Mean Local Roughness 0.01
Roughness Uniformity 0.017
Edge Density 0.019
Mean Gradient Magnitude 0.085
Gradient Variance 0.034
Gradient Smoothness 0.0
Directional Coherence 0.051
Pattern Complexity 0.111
Pattern Repetition 1.0
Detail Frequency Ratio 0.601
Spatial Variation 0.056
Texture Consistency 0.583

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.72
Brightness Variance 0.139
Brightness Uniformity 0.807
Brightness Skewness -2.586
Brightness Entropy 6.3
Rms Contrast 0.139
Michelson Contrast 1.0
Weber Contrast 0.325
Mean Local Contrast 0.011
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.388
Shadow Percentage 4.267
Midtone Percentage 12.003
Highlight Percentage 83.73
Shadow Clipping 0.004
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.014
Coarse Contrast 0.025
Multiscale Contrast Ratio 0.215
Edge Contrast 0.085
Contrast Clustering 0.417

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.737
Color Clustering 0.828
Color Transition Smoothness 0.78
Transition Uniformity 0.763
Sharp Transition Ratio 0.1
Transition Directionality 0.065
Mean Saturation 0.158
Saturation Variance 0.01
Low Saturation Ratio 0.916
Medium Saturation Ratio 0.084
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.745
Complementary Balance 0.042
Analogous Dominance 0.825
Temperature Bias 0.835

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 (2025). A minor - Research on Harmony - Variation 8 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0843.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/a-minor-research-on-harmony-variation-8_9c2.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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