AQC0797

Nanopublication — Computational Image Analysis - AQC0797

by Arnaud Quercy · Terres d Oliviers - Parfum de feuilles · 2024

Claim 1: Computational Image Analysis - AQC0797

Computational image analysis [3] of artwork Terres [1] d Oliviers - Parfum de feuilles (AQC0797) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 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]: 2384x3576 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank	Hex	%	Family	Name
1	537C65	16.2	yellow-green	dimgray
2	A4B9B2	16.1	green	steel gray
3	669280	14.8	green	blue gray
4	B9CEC8	12.7	green	silver
5	3E6348	11.1	yellow-green	darkslategray
6	87A896	11.0	yellow-green	darkseagreen
7	8A8EAD	6.8	violet	lightslategray
8	575D84	4.1	violet	dusty mauve
9	333D5B	4.0	blue-violet	grayish purple
10	1D332C	3.2	green	darkslategrey

Color Families:

Family	%
green	46.9
yellow-green	38.2
violet	10.9
blue-violet	4.0

Texture Analysis

Metric	Value
Global Roughness	0.171
Mean Local Roughness	0.02
Roughness Uniformity	0.014
Edge Density	0.118
Mean Gradient Magnitude	0.171
Gradient Variance	0.029
Gradient Smoothness	0.01
Directional Coherence	0.009
Pattern Complexity	0.111
Pattern Repetition	1.0
Detail Frequency Ratio	0.615
Spatial Variation	0.124
Texture Consistency	0.626

Brightness & Contrast Analysis

Metric	Value
Mean Brightness	0.532
Brightness Variance	0.171
Brightness Uniformity	0.679
Brightness Skewness	-0.189
Brightness Entropy	7.386
Rms Contrast	0.171
Michelson Contrast	1.0
Weber Contrast	0.591
Mean Local Contrast	0.022
Contrast Uniformity	0.355
Dynamic Range	0.984
Effective Dynamic Range	0.537
Shadow Percentage	12.837
Midtone Percentage	59.904
Highlight Percentage	27.259
Shadow Clipping	0.0
Highlight Clipping	0.0
Tonal Balance	0.176
Fine Contrast	0.01
Medium Contrast	0.027
Coarse Contrast	0.043
Multiscale Contrast Ratio	0.242
Edge Contrast	0.171
Contrast Clustering	0.374

Spatial Distribution Analysis

Metric	Value
Spatial Coherence	0.735
Color Clustering	0.84
Color Transition Smoothness	0.561
Transition Uniformity	0.807
Sharp Transition Ratio	0.1
Transition Directionality	0.01
Mean Saturation	0.259
Saturation Variance	0.016
Low Saturation Ratio	0.574
Medium Saturation Ratio	0.423
High Saturation Ratio	0.002
Saturation Clustering	1.0
Hue Concentration	0.81
Complementary Balance	0.0
Analogous Dominance	0.776
Temperature Bias	-0.921

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). Terres d Oliviers - Parfum de feuilles — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0797.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/terres-d-oliviers-parfum-de-feuilles_8u6.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)

c82e975c7bbefcb3d4a54eeb5b4f1593f76c3d29ee02b962b23114cc2045e307