AQC0466

Nanopublication — Computational Image Analysis - AQC0466

by Arnaud Quercy · La plainte de Cybele - Variations 2 · 2023

Claim 1: Computational Image Analysis - AQC0466

Analysis record [3]: La plainte de Cybele [1] - Variations 2 (AQC0466) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-02-04.

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]: 510x720 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D5B592 21.5 orange tan
2 C59A7C 18.5 orange rosybrown
3 E0CFB0 12.5 yellow-orange wheat
4 B17961 12.4 orange indianred
5 5F423D 8.2 red-orange dark brown
6 80675E 7.6 orange dimgray
7 8B4A3B 6.9 red-orange burnt sienna
8 6D1715 6.5 red-orange maroon
9 3A1F1A 3.2 red-orange very dark red
10 84ABD3 2.7 blue-violet skyblue
11 160106 0.3 red black [Accent]
12 F5F1D1 0.3 yellow antiquewhite [Accent]

Color Families:

Family %
orange 60.0
red-orange 24.9
yellow-orange 12.5
blue-violet 2.7
red 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
160106 red black 8.0
F5F1D1 yellow antiquewhite 16.5

Texture Analysis

Metric Value
Global Roughness 0.205
Mean Local Roughness 0.041
Roughness Uniformity 0.019
Edge Density 0.258
Mean Gradient Magnitude 0.266
Gradient Variance 0.05
Gradient Smoothness 0.16
Directional Coherence 0.012
Pattern Complexity 0.134
Pattern Repetition 1.0
Detail Frequency Ratio 0.629
Spatial Variation 0.087
Texture Consistency 0.756

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.561
Brightness Variance 0.205
Brightness Uniformity 0.635
Brightness Skewness -0.53
Brightness Entropy 7.541
Rms Contrast 0.205
Michelson Contrast 1.0
Weber Contrast 0.688
Mean Local Contrast 0.036
Contrast Uniformity 0.541
Dynamic Range 0.988
Effective Dynamic Range 0.639
Shadow Percentage 18.346
Midtone Percentage 41.258
Highlight Percentage 40.396
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.248
Fine Contrast 0.031
Medium Contrast 0.046
Coarse Contrast 0.059
Multiscale Contrast Ratio 0.523
Edge Contrast 0.266
Contrast Clustering 0.244

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.688
Color Clustering 0.672
Color Transition Smoothness 0.325
Transition Uniformity 0.677
Sharp Transition Ratio 0.1
Transition Directionality 0.007
Mean Saturation 0.396
Saturation Variance 0.033
Low Saturation Ratio 0.283
Medium Saturation Ratio 0.644
High Saturation Ratio 0.073
Saturation Clustering 0.998
Hue Concentration 0.891
Complementary Balance 0.035
Analogous Dominance 0.947
Temperature Bias 0.928

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 (2023). La plainte de Cybele - Variations 2 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0466.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/la-plainte-de-cybele-variations-2_59g.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)

15ac880248158b55a0a478de9e8685638f292658d1c1e1efd86c5c764289bb51