AQC0838

Nanopublication — Computational Image Analysis - AQC0838

Claim 1: Computational Image Analysis - AQC0838

Computational image analysis [3] of artwork G Major [1] - Research on Harmony - Variation 5 (AQC0838) [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]: 2541x3388 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 B2C799 21.7 yellow-green steel gray
2 C3D5AB 19.9 yellow-green silver
3 A1B788 18.5 yellow-green darkseagreen
4 8EA477 13.6 yellow-green gray
5 D7E4C6 7.7 yellow-green lightgray
6 768A64 6.3 yellow-green grey
7 464948 4.3 gray darkslategray
8 92510D 4.0 orange russet
9 AE7021 2.4 orange darkgoldenrod
10 25281C 1.6 yellow-green very dark gray
11 C4A362 0.3 yellow-orange ochre [Accent]
12 6D6D29 0.3 yellow dark brown [Accent]
13 E3B5A7 0.3 red-orange tan [Accent]

Color Families:

Family %
yellow-green 89.3
orange 6.4
gray 4.3
yellow-orange 0.3
yellow 0.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
C4A362 yellow-orange ochre 38.2
6D6D29 yellow dark brown 38.3
E3B5A7 red-orange tan 19.8

Texture Analysis

Metric Value
Global Roughness 0.162
Mean Local Roughness 0.03
Roughness Uniformity 0.017
Edge Density 0.205
Mean Gradient Magnitude 0.249
Gradient Variance 0.046
Gradient Smoothness 0.14
Directional Coherence 0.005
Pattern Complexity 0.125
Pattern Repetition 1.0
Detail Frequency Ratio 0.62
Spatial Variation 0.083
Texture Consistency 0.692

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.665
Brightness Variance 0.162
Brightness Uniformity 0.756
Brightness Skewness -1.185
Brightness Entropy 7.165
Rms Contrast 0.162
Michelson Contrast 1.0
Weber Contrast 0.498
Mean Local Contrast 0.032
Contrast Uniformity 0.457
Dynamic Range 1.0
Effective Dynamic Range 0.545
Shadow Percentage 5.932
Midtone Percentage 33.04
Highlight Percentage 61.028
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.018
Medium Contrast 0.04
Coarse Contrast 0.061
Multiscale Contrast Ratio 0.298
Edge Contrast 0.249
Contrast Clustering 0.308

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.705
Color Clustering 0.673
Color Transition Smoothness 0.392
Transition Uniformity 0.719
Sharp Transition Ratio 0.1
Transition Directionality 0.006
Mean Saturation 0.267
Saturation Variance 0.032
Low Saturation Ratio 0.787
Medium Saturation Ratio 0.149
High Saturation Ratio 0.063
Saturation Clustering 1.0
Hue Concentration 0.942
Complementary Balance 0.0
Analogous Dominance 0.986
Temperature Bias 0.115

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 (2025). G Major - Research on Harmony - Variation 5 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0838.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/g-major-research-on-harmony-variation-5_9a4.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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