AQC0699

Nanopublication — Computational Image Analysis - AQC0699

Claim 1: Computational Image Analysis - AQC0699

Computational image analysis [3] of artwork D Major [1] - Research on Harmony - Variation 4 (AQC0699) [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]: 2590x2590 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CD881C 30.8 orange darkgoldenrod
2 211C17 14.6 orange very dark gray
3 B49364 10.9 yellow-orange ochre
4 DE8A57 9.0 orange peru
5 AC6C2C 8.1 orange burnt sienna
6 9C5823 7.6 orange burnt sienna
7 4E3D2A 6.7 orange dark brown
8 D4B277 5.3 yellow-orange burlywood
9 6E5244 4.9 orange dark brown
10 4C6D33 2.0 yellow-green dark brown
11 62600B 0.3 yellow dark brown [Accent]

Color Families:

Family %
orange 81.7
yellow-orange 16.2
yellow-green 2.0
yellow 0.3

Accent Colors:

Hex Family Name Chroma
62600B yellow dark brown 43.9

Texture Analysis

Metric Value
Global Roughness 0.182
Mean Local Roughness 0.007
Roughness Uniformity 0.016
Edge Density 0.007
Mean Gradient Magnitude 0.049
Gradient Variance 0.021
Gradient Smoothness 0.0
Directional Coherence 0.209
Pattern Complexity 0.109
Pattern Repetition 1.0
Detail Frequency Ratio 0.631
Spatial Variation 0.136
Texture Consistency 0.361

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.462
Brightness Variance 0.182
Brightness Uniformity 0.606
Brightness Skewness -0.808
Brightness Entropy 6.726
Rms Contrast 0.182
Michelson Contrast 1.0
Weber Contrast 0.805
Mean Local Contrast 0.007
Contrast Uniformity 0.0
Dynamic Range 0.969
Effective Dynamic Range 0.573
Shadow Percentage 22.341
Midtone Percentage 71.885
Highlight Percentage 5.775
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.004
Medium Contrast 0.009
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.049
Contrast Clustering 0.639

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.746
Color Clustering 0.579
Color Transition Smoothness 0.863
Transition Uniformity 0.854
Sharp Transition Ratio 0.1
Transition Directionality 0.221
Mean Saturation 0.61
Saturation Variance 0.054
Low Saturation Ratio 0.092
Medium Saturation Ratio 0.459
High Saturation Ratio 0.449
Saturation Clustering 0.999
Hue Concentration 0.972
Complementary Balance 0.0
Analogous Dominance 0.978
Temperature Bias 0.957

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). D Major - Research on Harmony - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0699.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major-research-on-harmony-variation-4_7s2.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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