AQC0783

Nanopublication — Computational Image Analysis - AQC0783

Claim 1: Computational Image Analysis - AQC0783

The artwork Eb Minor [1] - Research on Harmony - Variation 7 (AQC0783) [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]: 2458x3688 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 383A49 26.2 violet dusty mauve
2 1F232D 11.1 blue-violet very dark gray
3 80D19F 9.3 yellow-green mediumaquamarine
4 9E87CA 9.3 violet mediumpurple
5 CBC6B6 8.7 yellow silver
6 70BB8A 8.3 yellow-green darkseagreen
7 A7AFAB 8.2 gray steel gray
8 6E5B8F 7.9 violet dusty mauve
9 399263 7.6 yellow-green seagreen
10 C4BBE9 3.5 violet lightsteelblue
11 8A7252 0.3 yellow-orange dimgray [Accent]
12 0D1F1A 0.3 green very dark gray [Accent]
13 3F6A6B 0.3 blue-green darkslategray [Accent]

Color Families:

Family %
violet 46.9
yellow-green 25.2
blue-violet 11.1
yellow 8.7
gray 8.2
yellow-orange 0.3
green 0.3
blue-green 0.3

Accent Colors:

Hex Family Name Chroma
8A7252 yellow-orange dimgray 21.6
0D1F1A green very dark gray 9.1
3F6A6B blue-green darkslategray 15.8

Texture Analysis

Metric Value
Global Roughness 0.227
Mean Local Roughness 0.009
Roughness Uniformity 0.011
Edge Density 0.025
Mean Gradient Magnitude 0.1
Gradient Variance 0.027
Gradient Smoothness 0.0
Directional Coherence 0.033
Pattern Complexity 0.114
Pattern Repetition 1.0
Detail Frequency Ratio 0.562
Spatial Variation 0.174
Texture Consistency 0.431

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.464
Brightness Variance 0.227
Brightness Uniformity 0.511
Brightness Skewness -0.072
Brightness Entropy 7.37
Rms Contrast 0.227
Michelson Contrast 1.0
Weber Contrast 0.758
Mean Local Contrast 0.012
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.635
Shadow Percentage 37.518
Midtone Percentage 34.897
Highlight Percentage 27.585
Shadow Clipping 0.004
Highlight Clipping 0.0
Tonal Balance 0.067
Fine Contrast 0.004
Medium Contrast 0.014
Coarse Contrast 0.031
Multiscale Contrast Ratio 0.142
Edge Contrast 0.1
Contrast Clustering 0.569

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.774
Color Clustering 0.83
Color Transition Smoothness 0.729
Transition Uniformity 0.808
Sharp Transition Ratio 0.1
Transition Directionality 0.044
Mean Saturation 0.309
Saturation Variance 0.024
Low Saturation Ratio 0.445
Medium Saturation Ratio 0.534
High Saturation Ratio 0.021
Saturation Clustering 1.0
Hue Concentration 0.63
Complementary Balance 0.006
Analogous Dominance 0.62
Temperature Bias -0.602

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). Eb Minor - Research on Harmony - Variation 7 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0783.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/eb-minor-research-on-harmony-variation-7_8oq.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)

3c900a520936fcebb067525f6a14693fc301e97a731b0bb6c463017568664f1d