AQC0508

Nanopublication — Computational Image Analysis - AQC0508

by Arnaud Quercy · Promenade aux jardins du Luxembourg, l'été · 2024

Claim 1: Computational Image Analysis - AQC0508

Analysis record [3]: Promenade [1] aux jardins du Luxembourg, l'été (AQC0508) [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]: 1638x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DAC7B1 20.8 yellow-orange silver
2 C7B49D 15.4 yellow-orange tan
3 DB8A44 14.8 orange peru
4 251D1A 12.8 red-orange very dark gray
5 57251F 11.2 red-orange russet
6 8F140D 9.2 red-orange darkred
7 873330 6.5 red-orange brown
8 4C3441 3.6 red-violet dusty mauve
9 DB6B07 3.6 orange chocolate
10 8F6E76 2.1 red gray

Color Families:

Family %
red-orange 39.7
yellow-orange 36.2
orange 18.4
red-violet 3.6
red 2.1

Texture Analysis

Metric Value
Global Roughness 0.262
Mean Local Roughness 0.027
Roughness Uniformity 0.029
Edge Density 0.104
Mean Gradient Magnitude 0.196
Gradient Variance 0.074
Gradient Smoothness 0.0
Directional Coherence 0.01
Pattern Complexity 0.11
Pattern Repetition 1.0
Detail Frequency Ratio 0.629
Spatial Variation 0.153
Texture Consistency 0.661

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.482
Brightness Variance 0.262
Brightness Uniformity 0.457
Brightness Skewness -0.11
Brightness Entropy 7.322
Rms Contrast 0.262
Michelson Contrast 1.0
Weber Contrast 0.822
Mean Local Contrast 0.027
Contrast Uniformity 0.036
Dynamic Range 0.992
Effective Dynamic Range 0.698
Shadow Percentage 41.959
Midtone Percentage 22.03
Highlight Percentage 36.012
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.041
Fine Contrast 0.015
Medium Contrast 0.034
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.337
Edge Contrast 0.196
Contrast Clustering 0.339

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.693
Color Clustering 0.598
Color Transition Smoothness 0.499
Transition Uniformity 0.504
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.463
Saturation Variance 0.081
Low Saturation Ratio 0.45
Medium Saturation Ratio 0.318
High Saturation Ratio 0.231
Saturation Clustering 0.998
Hue Concentration 0.944
Complementary Balance 0.0
Analogous Dominance 0.969
Temperature Bias 0.986

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). Promenade aux jardins du Luxembourg, l'été — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0508.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/promenade-aux-jardins-du-luxembourg-lete_5ps.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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