AQC0762

Nanopublication — Computational Image Analysis - AQC0762

Claim 1: Computational Image Analysis - AQC0762

Computational image analysis [3] of artwork G Minor [1] - Research on Harmony - Variation 5 (AQC0762) [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]: 2955x3940 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DAB381 16.0 yellow-orange burlywood
2 B2A99D 14.8 yellow-orange steel gray
3 1E191D 14.6 gray very dark gray
4 B19BC9 12.3 violet steel gray
5 CBBCAF 9.8 orange silver
6 C0432A 9.6 red-orange burnt sienna
7 DB8121 9.0 orange chocolate
8 E3933B 9.0 orange peru
9 4F3B68 3.1 violet dusty mauve
10 8F4C2A 1.8 orange burnt sienna
11 DEE1F3 0.3 blue-violet lavender [Accent]
12 BA7696 0.3 red dusty mauve [Accent]
13 9E7998 0.3 red-violet dusty mauve [Accent]

Color Families:

Family %
yellow-orange 30.8
orange 29.5
violet 15.4
gray 14.6
red-orange 9.6
blue-violet 0.3
red 0.3
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
DEE1F3 blue-violet lavender 9.2
BA7696 red dusty mauve 31.6
9E7998 red-violet dusty mauve 22.8

Texture Analysis

Metric Value
Global Roughness 0.219
Mean Local Roughness 0.012
Roughness Uniformity 0.013
Edge Density 0.038
Mean Gradient Magnitude 0.116
Gradient Variance 0.028
Gradient Smoothness 0.0
Directional Coherence 0.023
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.589
Spatial Variation 0.175
Texture Consistency 0.483

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.547
Brightness Variance 0.219
Brightness Uniformity 0.599
Brightness Skewness -1.047
Brightness Entropy 6.956
Rms Contrast 0.219
Michelson Contrast 1.0
Weber Contrast 0.842
Mean Local Contrast 0.015
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.667
Shadow Percentage 17.954
Midtone Percentage 42.073
Highlight Percentage 39.973
Shadow Clipping 0.001
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.018
Coarse Contrast 0.032
Multiscale Contrast Ratio 0.182
Edge Contrast 0.116
Contrast Clustering 0.517

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.777
Color Clustering 0.661
Color Transition Smoothness 0.707
Transition Uniformity 0.809
Sharp Transition Ratio 0.1
Transition Directionality 0.03
Mean Saturation 0.4
Saturation Variance 0.08
Low Saturation Ratio 0.495
Medium Saturation Ratio 0.23
High Saturation Ratio 0.275
Saturation Clustering 1.0
Hue Concentration 0.68
Complementary Balance 0.001
Analogous Dominance 0.765
Temperature Bias 0.766

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). G Minor - Research on Harmony - Variation 5 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0762.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/g-minor-research-on-harmony-variation-5_8gk.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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