AQC0730

Nanopublication — Computational Image Analysis - AQC0730

Claim 1: Computational Image Analysis - AQC0730

Analysis record [3]: Eb Minor [1] - Research on Harmony - Variation 6 (AQC0730) [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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 B38AC9 27.2 red-violet mediumpurple
2 A77EBE 23.9 red-violet steel gray
3 C198D8 13.6 red-violet plum
4 765581 10.5 red-violet dusty mauve
5 5D376E 7.5 red-violet dusty mauve
6 9776AA 7.4 red-violet dusty mauve
7 D9B4EA 3.4 red-violet thistle
8 30472C 2.7 yellow-green darkslategray
9 241D2B 2.4 violet very dark gray
10 43684F 1.3 yellow-green darkslategrey
11 E4D6C3 0.3 yellow-orange lightgray [Accent]
12 82654E 0.3 orange dimgray [Accent]

Color Families:

Family %
red-violet 93.6
yellow-green 4.0
violet 2.4
yellow-orange 0.3
orange 0.3

Accent Colors:

Hex Family Name Chroma
E4D6C3 yellow-orange lightgray 11.2
82654E orange dimgray 20.1

Texture Analysis

Metric Value
Global Roughness 0.145
Mean Local Roughness 0.025
Roughness Uniformity 0.017
Edge Density 0.146
Mean Gradient Magnitude 0.196
Gradient Variance 0.039
Gradient Smoothness 0.0
Directional Coherence 0.008
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.642
Spatial Variation 0.107
Texture Consistency 0.478

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.54
Brightness Variance 0.145
Brightness Uniformity 0.731
Brightness Skewness -1.008
Brightness Entropy 6.838
Rms Contrast 0.145
Michelson Contrast 1.0
Weber Contrast 0.558
Mean Local Contrast 0.026
Contrast Uniformity 0.318
Dynamic Range 1.0
Effective Dynamic Range 0.459
Shadow Percentage 12.485
Midtone Percentage 74.96
Highlight Percentage 12.555
Shadow Clipping 0.007
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.013
Medium Contrast 0.033
Coarse Contrast 0.046
Multiscale Contrast Ratio 0.293
Edge Contrast 0.196
Contrast Clustering 0.522

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.738
Color Clustering 0.743
Color Transition Smoothness 0.509
Transition Uniformity 0.753
Sharp Transition Ratio 0.1
Transition Directionality 0.009
Mean Saturation 0.336
Saturation Variance 0.008
Low Saturation Ratio 0.258
Medium Saturation Ratio 0.736
High Saturation Ratio 0.006
Saturation Clustering 0.999
Hue Concentration 0.913
Complementary Balance 0.035
Analogous Dominance 0.957
Temperature Bias -0.005

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). Eb Minor - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0730.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/eb-minor-research-on-harmony-variation-6_844.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/10/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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