AQC0711

Nanopublication — Computational Image Analysis - AQC0711

by Arnaud Quercy · A Minor - Research on Harmony - Variation 3 · 2024

Claim 1: Computational Image Analysis - AQC0711

K-means clustering analysis [3] (10 colors) performed on artwork A Minor [1] - Research on Harmony - Variation 3 (AQC0711) [2] by Arnaud Quercy [2] on 2025-12-04. 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]: 3024x4032 pixels. Analysis date: 2025-12-04.

Color Analysis

Rank Color Hex % Family Name
1 AC7940 15.7 orange peru
2 D4B490 15.2 yellow-orange tan
3 E1C6E0 13.8 red-violet thistle
4 C7333D 13.0 red-orange crimson
5 A42A47 10.6 red brown
6 0F0B16 10.4 violet black
7 DCB5C2 9.7 red silver
8 2A2A3A 5.1 violet very dark gray
9 D5A047 4.0 yellow-orange goldenrod
10 CE687B 2.5 red palevioletred
11 595633 0.3 yellow dark brown [Accent]
12 474E67 0.3 blue-violet grayish purple [Accent]

Color Families:

Family %
red 22.8
yellow-orange 19.2
orange 15.7
violet 15.5
red-violet 13.8
red-orange 13.0
yellow 0.3
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
595633 yellow dark brown 21.6
474E67 blue-violet grayish purple 16.5

Texture Analysis

Metric Value
Global Roughness 0.249
Mean Local Roughness 0.017
Roughness Uniformity 0.019
Edge Density 0.054
Mean Gradient Magnitude 0.134
Gradient Variance 0.046
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.623
Spatial Variation 0.198
Texture Consistency 0.594

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.516
Brightness Variance 0.249
Brightness Uniformity 0.517
Brightness Skewness -0.401
Brightness Entropy 7.494
Rms Contrast 0.249
Michelson Contrast 1.0
Weber Contrast 0.87
Mean Local Contrast 0.018
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.788
Shadow Percentage 22.525
Midtone Percentage 38.486
Highlight Percentage 38.989
Shadow Clipping 0.007
Highlight Clipping 0.0
Tonal Balance 0.177
Fine Contrast 0.009
Medium Contrast 0.023
Coarse Contrast 0.033
Multiscale Contrast Ratio 0.282
Edge Contrast 0.134
Contrast Clustering 0.406

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.764
Color Clustering 0.698
Color Transition Smoothness 0.662
Transition Uniformity 0.681
Sharp Transition Ratio 0.1
Transition Directionality 0.02
Mean Saturation 0.479
Saturation Variance 0.056
Low Saturation Ratio 0.299
Medium Saturation Ratio 0.462
High Saturation Ratio 0.239
Saturation Clustering 0.998
Hue Concentration 0.671
Complementary Balance 0.037
Analogous Dominance 0.809
Temperature Bias 0.766

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). A Minor - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0711.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/a-minor-research-on-harmony-variation-3_7wq.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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