AQC0618

Nanopublication — Computational Image Analysis - AQC0618

Claim 1: Computational Image Analysis - AQC0618

Computational image analysis [3] of artwork Promenade [1] aux jardins du Luxembourg - Variation 4 (AQC0618) [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]: 1935x2580 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E0D7CC 25.3 yellow-orange lightgray
2 CBC7B4 17.8 yellow silver
3 B1B39F 11.8 yellow-green steel gray
4 E2A374 11.6 orange darksalmon
5 394645 7.1 green darkslategray
6 7C939F 7.0 blue lightslategray
7 626C68 6.0 green dimgray
8 99907B 4.8 yellow-orange gray
9 181410 4.2 black black
10 C09A33 4.2 yellow-orange peru
11 9DB2C5 0.3 blue-violet steel gray [Accent]

Color Families:

Family %
yellow-orange 34.3
yellow 17.8
green 13.2
yellow-green 11.8
orange 11.6
blue 7.0
black 4.2
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
9DB2C5 blue-violet steel gray 12.4

Texture Analysis

Metric Value
Global Roughness 0.21
Mean Local Roughness 0.026
Roughness Uniformity 0.025
Edge Density 0.125
Mean Gradient Magnitude 0.217
Gradient Variance 0.091
Gradient Smoothness 0.0
Directional Coherence 0.005
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.61
Spatial Variation 0.112
Texture Consistency 0.77

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.656
Brightness Variance 0.21
Brightness Uniformity 0.679
Brightness Skewness -1.252
Brightness Entropy 7.314
Rms Contrast 0.21
Michelson Contrast 1.0
Weber Contrast 0.644
Mean Local Contrast 0.028
Contrast Uniformity 0.051
Dynamic Range 1.0
Effective Dynamic Range 0.675
Shadow Percentage 11.108
Midtone Percentage 26.671
Highlight Percentage 62.221
Shadow Clipping 0.072
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.013
Medium Contrast 0.035
Coarse Contrast 0.058
Multiscale Contrast Ratio 0.232
Edge Contrast 0.217
Contrast Clustering 0.23

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.711
Color Clustering 0.697
Color Transition Smoothness 0.448
Transition Uniformity 0.365
Sharp Transition Ratio 0.1
Transition Directionality 0.007
Mean Saturation 0.236
Saturation Variance 0.041
Low Saturation Ratio 0.714
Medium Saturation Ratio 0.25
High Saturation Ratio 0.036
Saturation Clustering 0.998
Hue Concentration 0.4
Complementary Balance 0.235
Analogous Dominance 0.682
Temperature Bias 0.295

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 - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0618.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/promenade-aux-jardins-du-luxembourg-variation-4_6wk.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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