AQC0952

Nanopublication — Computational Image Analysis - AQC0952

Claim 1: Computational Image Analysis - AQC0952

The artwork A5 (Power [1] Chord) - Research on Harmony (AQC0952) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-03-04. 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]: 1943x2915 pixels. Analysis date: 2026-03-04.

Color Analysis

Rank Color Hex % Family Name
1 E6BD28 20.8 yellow-orange goldenrod
2 D1BD9A 15.5 yellow-orange tan
3 9A9E9F 13.4 gray steel gray
4 ACB0B1 11.6 gray steel gray
5 BD911E 11.2 yellow-orange darkgoldenrod
6 E0B56C 7.4 yellow-orange burlywood
7 DCD5BF 7.1 yellow-orange lightgray
8 CDAB52 5.9 yellow-orange ochre
9 3C362C 4.0 yellow-orange darkslategray
10 E07A27 3.2 orange chocolate
11 FEFBCC 0.3 yellow lemonchiffon [Accent]
12 BAC96D 0.3 yellow-green ochre [Accent]

Color Families:

Family %
yellow-orange 71.8
gray 24.9
orange 3.2
yellow 0.3
yellow-green 0.3

Accent Colors:

Hex Family Name Chroma
FEFBCC yellow lemonchiffon 23.8
BAC96D yellow-green ochre 47.9

Texture Analysis

Metric Value
Global Roughness 0.125
Mean Local Roughness 0.023
Roughness Uniformity 0.018
Edge Density 0.105
Mean Gradient Magnitude 0.194
Gradient Variance 0.05
Gradient Smoothness 0.0
Directional Coherence 0.003
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.635
Spatial Variation 0.061
Texture Consistency 0.621

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.673
Brightness Variance 0.125
Brightness Uniformity 0.815
Brightness Skewness -1.932
Brightness Entropy 6.65
Rms Contrast 0.125
Michelson Contrast 0.962
Weber Contrast 0.294
Mean Local Contrast 0.027
Contrast Uniformity 0.208
Dynamic Range 0.98
Effective Dynamic Range 0.322
Shadow Percentage 3.699
Midtone Percentage 33.824
Highlight Percentage 62.477
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.012
Medium Contrast 0.032
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.262
Edge Contrast 0.194
Contrast Clustering 0.379

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.687
Color Clustering 0.437
Color Transition Smoothness 0.522
Transition Uniformity 0.669
Sharp Transition Ratio 0.1
Transition Directionality 0.002
Mean Saturation 0.438
Saturation Variance 0.113
Low Saturation Ratio 0.472
Medium Saturation Ratio 0.171
High Saturation Ratio 0.357
Saturation Clustering 0.999
Hue Concentration 0.991
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 0.978

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 (2026). A5 (Power Chord) - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0952.html

[2] Quercy, A. (2026). A5 (Power Chord) - Research on Harmony - Gallery. https://artquamanima.com/en/artworks/2026/03/a5-power-chord-research-on-harmony_1yh4.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)

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