AQC0679

Nanopublication — Computational Image Analysis - AQC0679

by Arnaud Quercy · Ab Octaves - Reflexions 14 · 2024

Claim 1: Computational Image Analysis - AQC0679

K-means clustering analysis [3] (10 colors) performed on artwork Ab Octaves [1] - Reflexions 14 (AQC0679) [2] by Arnaud Quercy [2] on 2026-02-04. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

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]: 2422x3633 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 C1BDB2 23.6 yellow silver
2 CEC9BC 20.7 yellow-orange lightgray
3 C3C4C1 15.7 white lightgrey
4 B6B0A7 12.6 yellow-orange steel gray
5 CCCFCF 12.6 white thistle
6 866590 3.7 red-violet dusty mauve
7 35353F 3.0 violet dusty mauve
8 9B87A4 2.8 red-violet steel gray
9 764778 2.6 red-violet dusty mauve
10 5C5484 2.6 violet dusty mauve
11 796552 0.3 orange dimgray [Accent]
12 494E5E 0.3 blue-violet grayish purple [Accent]

Color Families:

Family %
yellow-orange 33.4
white 28.3
yellow 23.6
red-violet 9.2
violet 5.5
orange 0.3
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
796552 orange dimgray 14.9
494E5E blue-violet grayish purple 10.2

Texture Analysis

Metric Value
Global Roughness 0.143
Mean Local Roughness 0.009
Roughness Uniformity 0.013
Edge Density 0.02
Mean Gradient Magnitude 0.077
Gradient Variance 0.019
Gradient Smoothness 0.0
Directional Coherence 0.046
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.607
Spatial Variation 0.112
Texture Consistency 0.394

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.708
Brightness Variance 0.143
Brightness Uniformity 0.798
Brightness Skewness -2.162
Brightness Entropy 6.128
Rms Contrast 0.143
Michelson Contrast 1.0
Weber Contrast 0.437
Mean Local Contrast 0.01
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.463
Shadow Percentage 3.998
Midtone Percentage 11.645
Highlight Percentage 84.358
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.013
Coarse Contrast 0.021
Multiscale Contrast Ratio 0.247
Edge Contrast 0.077
Contrast Clustering 0.606

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.756
Color Clustering 0.83
Color Transition Smoothness 0.804
Transition Uniformity 0.87
Sharp Transition Ratio 0.1
Transition Directionality 0.063
Mean Saturation 0.098
Saturation Variance 0.009
Low Saturation Ratio 0.927
Medium Saturation Ratio 0.073
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.893
Complementary Balance 0.007
Analogous Dominance 0.975
Temperature Bias 0.128

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 Octaves - Reflexions 14 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0679.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/ab-octaves-reflexions-14_7ka.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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