AQC0800

Nanopublication — Computational Image Analysis - AQC0800

by Arnaud Quercy · The Tuscan Hills - Lines Dawn by Time and Wind · 2024

Claim 1: Computational Image Analysis - AQC0800

K-means clustering analysis [3] (10 colors) performed on artwork The [1] Tuscan Hills - Lines Dawn by Time and Wind (AQC0800) [2] by Arnaud Quercy [2] on 2026-02-04. 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]: 2508x3761 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 99B79A 15.7 yellow-green darkseagreen
2 8FA689 15.0 yellow-green steel gray
3 A6C7AA 14.8 yellow-green steel gray
4 82927B 12.6 yellow-green gray
5 717C6F 10.2 yellow-green dimgray
6 B5D9BD 9.0 yellow-green silver
7 5F675E 8.9 yellow-green dimgrey
8 4D4F46 5.6 yellow-green darkslategray
9 33352A 4.6 yellow-green darkslategrey
10 998E56 3.5 yellow grey

Color Families:

Family %
yellow-green 96.5
yellow 3.5

Texture Analysis

Metric Value
Global Roughness 0.16
Mean Local Roughness 0.025
Roughness Uniformity 0.015
Edge Density 0.167
Mean Gradient Magnitude 0.214
Gradient Variance 0.037
Gradient Smoothness 0.105
Directional Coherence 0.008
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.614
Spatial Variation 0.099
Texture Consistency 0.784

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.575
Brightness Variance 0.16
Brightness Uniformity 0.722
Brightness Skewness -0.632
Brightness Entropy 7.266
Rms Contrast 0.16
Michelson Contrast 1.0
Weber Contrast 0.552
Mean Local Contrast 0.027
Contrast Uniformity 0.457
Dynamic Range 0.992
Effective Dynamic Range 0.537
Shadow Percentage 9.028
Midtone Percentage 57.197
Highlight Percentage 33.774
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.045
Fine Contrast 0.015
Medium Contrast 0.034
Coarse Contrast 0.054
Multiscale Contrast Ratio 0.268
Edge Contrast 0.214
Contrast Clustering 0.216

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.705
Color Clustering 0.845
Color Transition Smoothness 0.461
Transition Uniformity 0.761
Sharp Transition Ratio 0.1
Transition Directionality 0.009
Mean Saturation 0.198
Saturation Variance 0.007
Low Saturation Ratio 0.915
Medium Saturation Ratio 0.085
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.771
Complementary Balance 0.017
Analogous Dominance 0.701
Temperature Bias -0.195

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). The Tuscan Hills - Lines Dawn by Time and Wind — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0800.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/the-tuscan-hills-lines-dawn-by-time-and-wind_8vc.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)

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