AQC0971

Nanopublication — Computational Image Analysis - AQC0971

by Arnaud Quercy · G minor 7 - Research on Harmony - Variation 2 · 2026

Claim 1: Computational Image Analysis - AQC0971

K-means clustering analysis [3] (10 colors) performed on artwork G minor 7 - Research [1] on Harmony - Variation 2 (AQC0971) [2] by Arnaud Quercy [2] on 2026-03-05. 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]: 1882x2823 pixels. Analysis date: 2026-03-05.

Color Analysis

Rank Color Hex % Family Name
1 DE967A 17.0 orange darksalmon
2 503945 14.4 red dusty mauve
3 EEA68A 12.6 orange lightsalmon
4 625A6A 10.3 violet dusty mauve
5 CAC8C2 10.3 white silver
6 CC8469 8.6 orange peru
7 302E32 8.2 gray darkslategray
8 807784 7.6 red-violet dusty mauve
9 EBEAE5 5.8 white white
10 A299A3 5.3 red-violet steel gray
11 4E1D13 0.3 red-orange very dark red [Accent]

Color Families:

Family %
orange 38.2
white 16.1
red 14.4
red-violet 12.9
violet 10.3
gray 8.2
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
4E1D13 red-orange very dark red 28.4

Texture Analysis

Metric Value
Global Roughness 0.221
Mean Local Roughness 0.048
Roughness Uniformity 0.031
Edge Density 0.28
Mean Gradient Magnitude 0.355
Gradient Variance 0.119
Gradient Smoothness 0.028
Directional Coherence 0.009
Pattern Complexity 0.129
Pattern Repetition 1.0
Detail Frequency Ratio 0.675
Spatial Variation 0.171
Texture Consistency 0.517

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.549
Brightness Variance 0.221
Brightness Uniformity 0.598
Brightness Skewness -0.247
Brightness Entropy 7.573
Rms Contrast 0.221
Michelson Contrast 1.0
Weber Contrast 0.716
Mean Local Contrast 0.05
Contrast Uniformity 0.349
Dynamic Range 1.0
Effective Dynamic Range 0.678
Shadow Percentage 24.169
Midtone Percentage 37.676
Highlight Percentage 38.154
Shadow Clipping 0.0
Highlight Clipping 0.07
Tonal Balance 0.24
Fine Contrast 0.029
Medium Contrast 0.061
Coarse Contrast 0.078
Multiscale Contrast Ratio 0.366
Edge Contrast 0.355
Contrast Clustering 0.483

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.793
Color Clustering 0.837
Color Transition Smoothness 0.104
Transition Uniformity 0.251
Sharp Transition Ratio 0.1
Transition Directionality 0.01
Mean Saturation 0.26
Saturation Variance 0.034
Low Saturation Ratio 0.518
Medium Saturation Ratio 0.481
High Saturation Ratio 0.001
Saturation Clustering 0.999
Hue Concentration 0.852
Complementary Balance 0.0
Analogous Dominance 0.907
Temperature Bias 0.924

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). G minor 7 - Research on Harmony - Variation 2 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0971.html

[2] Quercy, A. (2026). G minor 7 - Research on Harmony - Variation 2 - Gallery. https://artquamanima.com/en/artworks/2026/03/g-minor-7-research-on-harmony-variation-2_1ypq.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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