AQC0822

Nanopublication — Computational Image Analysis - AQC0822

Claim 1: Computational Image Analysis - AQC0822

Computational image analysis [3] of artwork D Major [1] - Research on Harmony - Variation 12 (AQC0822) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 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]: 2513x3350 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D5CDC4 20.2 yellow-orange lightgray
2 86A391 17.2 yellow-green darkseagreen
3 96B5A4 16.8 yellow-green steel gray
4 DED7CF 15.1 yellow-orange lightgrey
5 A9C8B8 10.8 yellow-green silver
6 728F7C 8.0 yellow-green gray
7 7C7019 5.4 yellow olive
8 998937 2.8 yellow olivedrab
9 191E19 2.7 gray very dark gray
10 434F44 1.2 yellow-green darkslategray
11 E6B69F 0.3 orange burlywood [Accent]
12 CFA398 0.3 red-orange tan [Accent]

Color Families:

Family %
yellow-green 53.9
yellow-orange 35.2
yellow 8.2
gray 2.7
orange 0.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
E6B69F orange burlywood 22.8
CFA398 red-orange tan 19.2

Texture Analysis

Metric Value
Global Roughness 0.165
Mean Local Roughness 0.017
Roughness Uniformity 0.017
Edge Density 0.093
Mean Gradient Magnitude 0.149
Gradient Variance 0.04
Gradient Smoothness 0.0
Directional Coherence 0.032
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.615
Spatial Variation 0.102
Texture Consistency 0.69

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.672
Brightness Variance 0.165
Brightness Uniformity 0.755
Brightness Skewness -1.246
Brightness Entropy 6.971
Rms Contrast 0.165
Michelson Contrast 1.0
Weber Contrast 0.439
Mean Local Contrast 0.019
Contrast Uniformity 0.043
Dynamic Range 1.0
Effective Dynamic Range 0.467
Shadow Percentage 3.75
Midtone Percentage 40.892
Highlight Percentage 55.358
Shadow Clipping 0.003
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.009
Medium Contrast 0.024
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.149
Contrast Clustering 0.31

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.716
Color Clustering 0.784
Color Transition Smoothness 0.628
Transition Uniformity 0.732
Sharp Transition Ratio 0.1
Transition Directionality 0.038
Mean Saturation 0.195
Saturation Variance 0.034
Low Saturation Ratio 0.894
Medium Saturation Ratio 0.05
High Saturation Ratio 0.056
Saturation Clustering 1.0
Hue Concentration 0.703
Complementary Balance 0.005
Analogous Dominance 0.695
Temperature Bias -0.462

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). D Major - Research on Harmony - Variation 12 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0822.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/d-major-research-on-harmony-variation-12_93w.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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