AQC0801

Nanopublication — Computational Image Analysis - AQC0801

by Arnaud Quercy · Breeze over Azure Walls - Sea and memories · 2024

Claim 1: Computational Image Analysis - AQC0801

The artwork Breeze [1] over Azure Walls - Sea and memories (AQC0801) [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]: 2309x3463 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank	Hex	%	Family	Name
1	B3B5B4	19.6	gray	steel gray
2	BCC2CC	15.6	blue-violet	silver
3	A8A495	12.8	yellow	steel gray
4	8DA5AC	10.0	blue-green	steel gray
5	7D7D91	8.5	violet	dusty mauve
6	95977B	7.9	yellow-green	gray
7	55696A	6.5	blue-green	dimgray
8	6D587C	6.5	violet	dusty mauve
9	4A4852	6.3	violet	dusty mauve
10	313237	6.3	gray	dusty mauve

Color Families:

Family	%
gray	25.8
violet	21.3
blue-green	16.5
blue-violet	15.6
yellow	12.8
yellow-green	7.9

Texture Analysis

Metric	Value
Global Roughness	0.172
Mean Local Roughness	0.013
Roughness Uniformity	0.013
Edge Density	0.028
Mean Gradient Magnitude	0.11
Gradient Variance	0.029
Gradient Smoothness	0.0
Directional Coherence	0.021
Pattern Complexity	0.119
Pattern Repetition	1.0
Detail Frequency Ratio	0.59
Spatial Variation	0.102
Texture Consistency	0.74

Brightness & Contrast Analysis

Metric	Value
Mean Brightness	0.572
Brightness Variance	0.172
Brightness Uniformity	0.7
Brightness Skewness	-0.803
Brightness Entropy	7.12
Rms Contrast	0.172
Michelson Contrast	1.0
Weber Contrast	0.599
Mean Local Contrast	0.014
Contrast Uniformity	0.0
Dynamic Range	0.902
Effective Dynamic Range	0.545
Shadow Percentage	12.268
Midtone Percentage	48.776
Highlight Percentage	38.955
Shadow Clipping	0.0
Highlight Clipping	0.0
Tonal Balance	0.0
Fine Contrast	0.007
Medium Contrast	0.018
Coarse Contrast	0.031
Multiscale Contrast Ratio	0.219
Edge Contrast	0.11
Contrast Clustering	0.26

Spatial Distribution Analysis

Metric	Value
Spatial Coherence	0.713
Color Clustering	0.898
Color Transition Smoothness	0.711
Transition Uniformity	0.799
Sharp Transition Ratio	0.1
Transition Directionality	0.028
Mean Saturation	0.153
Saturation Variance	0.011
Low Saturation Ratio	0.884
Medium Saturation Ratio	0.116
High Saturation Ratio	0.0
Saturation Clustering	1.0
Hue Concentration	0.423
Complementary Balance	0.05
Analogous Dominance	0.564
Temperature Bias	-0.261

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). Breeze over Azure Walls - Sea and memories — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0801.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/breeze-over-azure-walls-sea-and-memories_8vq.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 type	computational analysis
Voice	third person
Epistemic status	empirical measurement
Methodology	computational analysis
Certainty	high

Checksum (SHA-256)

822b42e3a4693343a6a2b67d43a3c311833815080822a9b14377e93061eabdb9