AQC0661

Nanopublication — Computational Image Analysis - AQC0661

Claim 1: Computational Image Analysis - AQC0661

The artwork Ab Major [1] - Research on Harmony - Variation 6 (AQC0661) [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]: 1919x2560 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 394B7F 16.1 violet dusty mauve
2 5E6277 13.3 blue-violet grayish purple
3 EC986D 12.1 orange darksalmon
4 1F1625 12.0 violet very dark gray
5 3B3634 12.0 gray darkslategray
6 E74111 11.1 red-orange orangered
7 C8ACA5 9.4 red-orange tan
8 7A5B98 9.1 violet dusty mauve
9 72A4C1 2.9 blue cadetblue
10 92542E 2.0 orange burnt sienna
11 F2E3BE 0.3 yellow-orange wheat [Accent]
12 E1D6B4 0.3 yellow wheat [Accent]
13 573863 0.3 red-violet dusty mauve [Accent]
14 955A62 0.3 red dimgray [Accent]

Color Families:

Family %
violet 37.3
red-orange 20.5
orange 14.1
blue-violet 13.3
gray 12.0
blue 2.9
yellow-orange 0.3
yellow 0.3
red-violet 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
F2E3BE yellow-orange wheat 20.0
E1D6B4 yellow wheat 18.1
573863 red-violet dusty mauve 29.7
955A62 red dimgray 25.7

Texture Analysis

Metric Value
Global Roughness 0.195
Mean Local Roughness 0.01
Roughness Uniformity 0.021
Edge Density 0.024
Mean Gradient Magnitude 0.068
Gradient Variance 0.033
Gradient Smoothness 0.0
Directional Coherence 0.312
Pattern Complexity 0.109
Pattern Repetition 1.0
Detail Frequency Ratio 0.645
Spatial Variation 0.098
Texture Consistency 0.706

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.398
Brightness Variance 0.195
Brightness Uniformity 0.511
Brightness Skewness 0.344
Brightness Entropy 7.224
Rms Contrast 0.195
Michelson Contrast 1.0
Weber Contrast 0.817
Mean Local Contrast 0.01
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.616
Shadow Percentage 39.821
Midtone Percentage 44.869
Highlight Percentage 15.311
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.013
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.068
Contrast Clustering 0.294

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.726
Color Clustering 0.48
Color Transition Smoothness 0.806
Transition Uniformity 0.764
Sharp Transition Ratio 0.1
Transition Directionality 0.301
Mean Saturation 0.45
Saturation Variance 0.056
Low Saturation Ratio 0.28
Medium Saturation Ratio 0.593
High Saturation Ratio 0.127
Saturation Clustering 1.0
Hue Concentration 0.353
Complementary Balance 0.138
Analogous Dominance 0.528
Temperature Bias 0.102

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). Ab Major - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0661.html

[2] Quercy, A. (2024). Ab Major - Research on Harmony - Variation 6 - Gallery. https://artquamanima.com/en/artworks/2024/01/ab-major-research-on-harmony-variation-6_7da.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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