AQC0651

Nanopublication — Computational Image Analysis - AQC0651

by Arnaud Quercy · B Major - Research on Harmony - Variation 1 · 2024

Claim 1: Computational Image Analysis - AQC0651

Analysis record [3]: B Major [1] - Research on Harmony - Variation 1 (AQC0651) [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]: 2009x3013 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 93CA44 20.1 yellow-green yellowgreen
2 4C4454 15.4 violet dusty mauve
3 3D3741 15.3 red-violet dusty mauve
4 5BAD4E 12.4 yellow-green mediumseagreen
5 2C2827 12.3 gray very dark gray
6 A7D559 8.4 yellow-green ochre
7 625966 6.3 red-violet dusty mauve
8 E7E5D8 4.8 yellow white
9 0E1008 3.0 black black
10 878383 1.9 gray gray
11 5D4710 0.3 yellow-orange russet [Accent]

Color Families:

Family %
yellow-green 40.9
red-violet 21.6
violet 15.4
gray 14.2
yellow 4.8
black 3.0
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
5D4710 yellow-orange russet 34.1

Texture Analysis

Metric Value
Global Roughness 0.235
Mean Local Roughness 0.021
Roughness Uniformity 0.028
Edge Density 0.085
Mean Gradient Magnitude 0.181
Gradient Variance 0.086
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.108
Pattern Repetition 1.0
Detail Frequency Ratio 0.62
Spatial Variation 0.167
Texture Consistency 0.523

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.441
Brightness Variance 0.235
Brightness Uniformity 0.468
Brightness Skewness 0.237
Brightness Entropy 7.386
Rms Contrast 0.235
Michelson Contrast 1.0
Weber Contrast 0.77
Mean Local Contrast 0.024
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.655
Shadow Percentage 46.351
Midtone Percentage 26.803
Highlight Percentage 26.846
Shadow Clipping 0.034
Highlight Clipping 0.013
Tonal Balance 0.004
Fine Contrast 0.011
Medium Contrast 0.031
Coarse Contrast 0.053
Multiscale Contrast Ratio 0.208
Edge Contrast 0.181
Contrast Clustering 0.477

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.722
Color Clustering 0.687
Color Transition Smoothness 0.505
Transition Uniformity 0.378
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.387
Saturation Variance 0.053
Low Saturation Ratio 0.48
Medium Saturation Ratio 0.488
High Saturation Ratio 0.032
Saturation Clustering 0.998
Hue Concentration 0.389
Complementary Balance 0.142
Analogous Dominance 0.616
Temperature Bias 0.098

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). B Major - Research on Harmony - Variation 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0651.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/b-major-research-on-harmony-variation-1_79e.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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