AQC0448

Nanopublication — Computational Image Analysis - AQC0448

by Arnaud Quercy · Three Flowers · 2023

Claim 1: Computational Image Analysis - AQC0448

Computational image analysis [3] of artwork Three [1] Flowers (AQC0448) [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]: 720x1008 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 1A0F1D 18.4 red-violet very dark gray
2 761F12 16.8 red-orange maroon
3 A33824 15.6 red-orange brown
4 C84A32 11.8 red-orange chocolate
5 C7896A 9.4 orange rosybrown
6 AB7156 9.4 orange indianred
7 4E4C5A 8.7 violet dusty mauve
8 766F71 4.3 gray dimgray
9 B2A39B 2.8 orange steel gray
10 E4D9D0 2.8 orange gainsboro
11 412833 0.3 red darkslategray [Accent]

Color Families:

Family %
red-orange 44.1
orange 24.4
red-violet 18.4
violet 8.7
gray 4.3
red 0.3

Accent Colors:

Hex Family Name Chroma
412833 red darkslategray 14.1

Texture Analysis

Metric Value
Global Roughness 0.192
Mean Local Roughness 0.009
Roughness Uniformity 0.012
Edge Density 0.025
Mean Gradient Magnitude 0.068
Gradient Variance 0.017
Gradient Smoothness 0.0
Directional Coherence 0.185
Pattern Complexity 0.112
Pattern Repetition 1.0
Detail Frequency Ratio 0.593
Spatial Variation 0.145
Texture Consistency 0.646

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.347
Brightness Variance 0.192
Brightness Uniformity 0.447
Brightness Skewness 0.403
Brightness Entropy 7.457
Rms Contrast 0.192
Michelson Contrast 0.992
Weber Contrast 0.868
Mean Local Contrast 0.009
Contrast Uniformity 0.0
Dynamic Range 0.961
Effective Dynamic Range 0.604
Shadow Percentage 48.305
Midtone Percentage 47.292
Highlight Percentage 4.403
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.185
Fine Contrast 0.005
Medium Contrast 0.012
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.068
Contrast Clustering 0.354

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.748
Color Clustering 0.601
Color Transition Smoothness 0.806
Transition Uniformity 0.888
Sharp Transition Ratio 0.1
Transition Directionality 0.155
Mean Saturation 0.572
Saturation Variance 0.065
Low Saturation Ratio 0.178
Medium Saturation Ratio 0.382
High Saturation Ratio 0.44
Saturation Clustering 1.0
Hue Concentration 0.73
Complementary Balance 0.0
Analogous Dominance 0.781
Temperature Bias 0.742

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 (2023). Three Flowers — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0448.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/three-flowers_52g.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)

9dc207a91395c25943cb8f0450afb2f368260730f2be4417b479e060996c582c