AQC0588

Nanopublication — Computational Image Analysis - AQC0588

Claim 1: Computational Image Analysis - AQC0588

Computational image analysis [3] of artwork C# Major [1] - Research on Harmony - Variation 1 (AQC0588) [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]: 2501x3335 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 73415B 24.2 red dusty mauve
2 64364E 20.5 red dusty mauve
3 83516A 13.8 red dusty mauve
4 6CE2E3 12.4 blue-green skyblue
5 60CFD0 8.7 blue-green mediumturquoise
6 96697F 7.4 red dusty mauve
7 F2E3E1 4.6 red-orange white
8 B0879C 4.5 red rosybrown
9 D1ACC0 2.9 red-violet silver
10 1F1F29 0.9 violet very dark gray
11 115EAE 0.3 blue-violet darkcyan [Accent]
12 2A4858 0.3 blue darkslategray [Accent]
13 20605B 0.3 green darkslategray [Accent]

Color Families:

Family %
red 70.5
blue-green 21.1
red-orange 4.6
red-violet 2.9
violet 0.9
blue-violet 0.3
blue 0.3
green 0.3

Accent Colors:

Hex Family Name Chroma
115EAE blue-violet darkcyan 49.8
2A4858 blue darkslategray 14.3
20605B green darkslategray 21.2

Texture Analysis

Metric Value
Global Roughness 0.208
Mean Local Roughness 0.061
Roughness Uniformity 0.06
Edge Density 0.204
Mean Gradient Magnitude 0.422
Gradient Variance 0.285
Gradient Smoothness 0.0
Directional Coherence 0.017
Pattern Complexity 0.128
Pattern Repetition 1.0
Detail Frequency Ratio 0.718
Spatial Variation 0.115
Texture Consistency 0.72

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.469
Brightness Variance 0.208
Brightness Uniformity 0.557
Brightness Skewness 0.682
Brightness Entropy 7.123
Rms Contrast 0.208
Michelson Contrast 1.0
Weber Contrast 0.639
Mean Local Contrast 0.062
Contrast Uniformity 0.031
Dynamic Range 1.0
Effective Dynamic Range 0.592
Shadow Percentage 36.998
Midtone Percentage 35.635
Highlight Percentage 27.367
Shadow Clipping 0.005
Highlight Clipping 0.012
Tonal Balance 0.0
Fine Contrast 0.039
Medium Contrast 0.076
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.422
Contrast Clustering 0.28

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.702
Color Clustering 0.78
Color Transition Smoothness 0.0
Transition Uniformity 0.0
Sharp Transition Ratio 0.1
Transition Directionality 0.019
Mean Saturation 0.414
Saturation Variance 0.017
Low Saturation Ratio 0.176
Medium Saturation Ratio 0.82
High Saturation Ratio 0.005
Saturation Clustering 0.997
Hue Concentration 0.562
Complementary Balance 0.002
Analogous Dominance 0.76
Temperature Bias 0.522

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). C# Major - Research on Harmony - Variation 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0588.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-major-research-on-harmony-variation-1_6kw.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)

5ac17cea64ac87b509e680e7315710bd0e5ec1718afa12b2f12d1bb5ae0b2c71