AQC0820

Nanopublication — Computational Image Analysis - AQC0820

Claim 1: Computational Image Analysis - AQC0820

The artwork C Minor [1] - Research on Harmony - Variation 9 (AQC0820) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-02-04. 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]: 2473x3297 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E5B197 23.7 orange burlywood
2 DFA487 17.9 orange tan
3 97725B 14.9 orange gray
4 ECBFA7 13.4 orange lightpink
5 AA856D 11.9 orange rosybrown
6 805C47 7.2 orange burnt sienna
7 D59273 6.7 orange darksalmon
8 926D86 2.4 red-violet dusty mauve
9 3C2218 1.3 orange very dark orange
10 C34B1C 0.6 orange chocolate
11 1C0A03 0.3 red-orange black [Accent]
12 B8929C 0.3 red rosybrown [Accent]

Color Families:

Family %
orange 97.6
red-violet 2.4
red-orange 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
1C0A03 red-orange black 7.8
B8929C red rosybrown 16.0

Texture Analysis

Metric Value
Global Roughness 0.142
Mean Local Roughness 0.012
Roughness Uniformity 0.012
Edge Density 0.045
Mean Gradient Magnitude 0.108
Gradient Variance 0.023
Gradient Smoothness 0.0
Directional Coherence 0.027
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.599
Spatial Variation 0.111
Texture Consistency 0.526

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.635
Brightness Variance 0.142
Brightness Uniformity 0.777
Brightness Skewness -0.847
Brightness Entropy 6.811
Rms Contrast 0.142
Michelson Contrast 0.992
Weber Contrast 0.432
Mean Local Contrast 0.013
Contrast Uniformity 0.0
Dynamic Range 0.984
Effective Dynamic Range 0.396
Shadow Percentage 2.006
Midtone Percentage 42.143
Highlight Percentage 55.851
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.017
Coarse Contrast 0.029
Multiscale Contrast Ratio 0.202
Edge Contrast 0.108
Contrast Clustering 0.474

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.712
Color Clustering 0.589
Color Transition Smoothness 0.723
Transition Uniformity 0.846
Sharp Transition Ratio 0.1
Transition Directionality 0.033
Mean Saturation 0.373
Saturation Variance 0.007
Low Saturation Ratio 0.13
Medium Saturation Ratio 0.86
High Saturation Ratio 0.01
Saturation Clustering 1.0
Hue Concentration 0.986
Complementary Balance 0.0
Analogous Dominance 0.995
Temperature Bias 0.999

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). C Minor - Research on Harmony - Variation 9 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0820.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/c-minor-research-on-harmony-variation-9_934.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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