AQC0599

Nanopublication — Computational Image Analysis - AQC0599

by Arnaud Quercy · F minor - Research on Harmony - Variation 5 · 2024

Claim 1: Computational Image Analysis - AQC0599

The artwork F minor - Research [1] on Harmony - Variation 5 (AQC0599) [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]: 2599x3264 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 371B2B 23.7 red-violet very dark purple
2 D09791 17.5 red-orange rosybrown
3 DFA8A3 15.3 red-orange tan
4 BE8580 14.3 red-orange palevioletred
5 482C3A 8.7 red dusty mauve
6 1C1B2B 6.4 violet very dark gray
7 E0CDC9 5.0 red-orange lightgray
8 5F4852 4.8 red dusty mauve
9 8F6F70 3.1 red-orange gray
10 AA451E 1.2 orange burnt sienna
11 A4AFB6 0.3 blue steel gray [Accent]

Color Families:

Family %
red-orange 55.2
red-violet 23.7
red 13.5
violet 6.4
orange 1.2
blue 0.3

Accent Colors:

Hex Family Name Chroma
A4AFB6 blue steel gray 5.8

Texture Analysis

Metric Value
Global Roughness 0.254
Mean Local Roughness 0.019
Roughness Uniformity 0.024
Edge Density 0.083
Mean Gradient Magnitude 0.133
Gradient Variance 0.044
Gradient Smoothness 0.0
Directional Coherence 0.161
Pattern Complexity 0.145
Pattern Repetition 1.0
Detail Frequency Ratio 0.677
Spatial Variation 0.215
Texture Consistency 0.285

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.447
Brightness Variance 0.254
Brightness Uniformity 0.432
Brightness Skewness -0.102
Brightness Entropy 7.155
Rms Contrast 0.254
Michelson Contrast 1.0
Weber Contrast 0.818
Mean Local Contrast 0.019
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.659
Shadow Percentage 42.522
Midtone Percentage 29.365
Highlight Percentage 28.113
Shadow Clipping 0.0
Highlight Clipping 0.002
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.023
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.133
Contrast Clustering 0.715

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.76
Color Clustering 0.805
Color Transition Smoothness 0.658
Transition Uniformity 0.718
Sharp Transition Ratio 0.1
Transition Directionality 0.172
Mean Saturation 0.354
Saturation Variance 0.018
Low Saturation Ratio 0.34
Medium Saturation Ratio 0.649
High Saturation Ratio 0.011
Saturation Clustering 1.0
Hue Concentration 0.852
Complementary Balance 0.001
Analogous Dominance 0.908
Temperature Bias 0.891

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). F minor - Research on Harmony - Variation 5 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0599.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/f-minor-research-on-harmony-variation-5_6p6.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)

f75263720c3d04ef6c8a1bd62d3a6124c3c4463c8430c65d4ce6c0cf9764c176