AQC0463

Nanopublication — Computational Image Analysis - AQC0463

Claim 1: Computational Image Analysis - AQC0463

Computational image analysis [3] of artwork Alaska [1] (AQC0463) [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]: 526x701 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 B3BACB 21.6 blue-violet silver
2 A1A9B7 18.7 blue-violet steel gray
3 8B95A3 15.3 blue-violet lightslategray
4 6C8190 12.5 blue grayish purple
5 4F6A78 10.0 blue dimgray
6 929D80 5.9 yellow-green gray
7 7B8756 5.5 yellow-green dimgrey
8 244B64 4.9 blue-violet grayish purple
9 616F30 3.6 yellow-green dark brown
10 142B26 2.0 green very dark gray
11 46331F 0.3 orange dark brown [Accent]
12 433E28 0.3 yellow darkslategray [Accent]

Color Families:

Family %
blue-violet 60.5
blue 22.5
yellow-green 15.0
green 2.0
orange 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
46331F orange dark brown 17.1
433E28 yellow darkslategray 15.1

Texture Analysis

Metric Value
Global Roughness 0.148
Mean Local Roughness 0.029
Roughness Uniformity 0.021
Edge Density 0.149
Mean Gradient Magnitude 0.197
Gradient Variance 0.045
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.127
Pattern Repetition 1.0
Detail Frequency Ratio 0.632
Spatial Variation 0.08
Texture Consistency 0.655

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.563
Brightness Variance 0.148
Brightness Uniformity 0.737
Brightness Skewness -0.813
Brightness Entropy 7.07
Rms Contrast 0.148
Michelson Contrast 1.0
Weber Contrast 0.505
Mean Local Contrast 0.027
Contrast Uniformity 0.328
Dynamic Range 0.898
Effective Dynamic Range 0.463
Shadow Percentage 7.638
Midtone Percentage 61.147
Highlight Percentage 31.215
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.019
Medium Contrast 0.034
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.428
Edge Contrast 0.197
Contrast Clustering 0.345

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.709
Color Clustering 0.732
Color Transition Smoothness 0.491
Transition Uniformity 0.698
Sharp Transition Ratio 0.1
Transition Directionality 0.013
Mean Saturation 0.231
Saturation Variance 0.033
Low Saturation Ratio 0.758
Medium Saturation Ratio 0.205
High Saturation Ratio 0.037
Saturation Clustering 0.999
Hue Concentration 0.543
Complementary Balance 0.02
Analogous Dominance 0.692
Temperature Bias -0.681

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). Alaska — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0463.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/alaska_58a.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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