AQC0339

Nanopublication — Computational Image Analysis - AQC0339

by Arnaud Quercy · The Monk's garden · 2022

Claim 1: Computational Image Analysis - AQC0339

The [1] artwork The Monk's garden (AQC0339) [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]: 2760x3681 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 090604 19.0 black black
2 755B37 12.0 yellow-orange dark brown
3 4D4434 11.8 yellow-orange dark brown
4 D98F5F 10.7 orange darksalmon
5 30271E 10.6 yellow-orange very dark gray
6 D05E31 8.8 orange chocolate
7 B17F3F 8.6 orange peru
8 B43525 8.0 red-orange brown
9 7F2C20 7.9 red-orange russet
10 91948C 2.5 gray gray
11 495F6A 0.3 blue dimgray [Accent]
12 BCAA4E 0.3 yellow ochre [Accent]

Color Families:

Family %
yellow-orange 34.4
orange 28.1
black 19.0
red-orange 15.9
gray 2.5
blue 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
495F6A blue dimgray 10.3
BCAA4E yellow ochre 49.3

Texture Analysis

Metric Value
Global Roughness 0.199
Mean Local Roughness 0.019
Roughness Uniformity 0.01
Edge Density 0.059
Mean Gradient Magnitude 0.135
Gradient Variance 0.014
Gradient Smoothness 0.116
Directional Coherence 0.026
Pattern Complexity 0.136
Pattern Repetition 1.0
Detail Frequency Ratio 0.632
Spatial Variation 0.095
Texture Consistency 0.783

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.319
Brightness Variance 0.199
Brightness Uniformity 0.375
Brightness Skewness 0.013
Brightness Entropy 7.344
Rms Contrast 0.199
Michelson Contrast 1.0
Weber Contrast 0.967
Mean Local Contrast 0.018
Contrast Uniformity 0.459
Dynamic Range 0.914
Effective Dynamic Range 0.627
Shadow Percentage 52.688
Midtone Percentage 44.59
Highlight Percentage 2.723
Shadow Clipping 0.329
Highlight Clipping 0.0
Tonal Balance 0.026
Fine Contrast 0.013
Medium Contrast 0.022
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.135
Contrast Clustering 0.217

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.701
Color Clustering 0.506
Color Transition Smoothness 0.641
Transition Uniformity 0.888
Sharp Transition Ratio 0.1
Transition Directionality 0.035
Mean Saturation 0.521
Saturation Variance 0.073
Low Saturation Ratio 0.225
Medium Saturation Ratio 0.498
High Saturation Ratio 0.276
Saturation Clustering 0.996
Hue Concentration 0.903
Complementary Balance 0.026
Analogous Dominance 0.963
Temperature Bias 0.917

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 (2022). The Monk's garden — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0339.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2022/01/the-monks-garden_3w2.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)

c2b704fcbed9920d07904ea49c35f33111aa849c60d8515657276f5ad0bb8908