AQC0721

Nanopublication — Computational Image Analysis - AQC0721

by Arnaud Quercy · C Minor - Research on Harmony - Variation 6 · 2024

Claim 1: Computational Image Analysis - AQC0721

Analysis record [3]: C Minor [1] - Research on Harmony - Variation 6 (AQC0721) [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 6E497D 18.2 red-violet dusty mauve
2 886595 16.2 red-violet dusty mauve
3 D9294B 14.1 red-orange crimson
4 E54467 11.7 red indianred
5 A78BD2 11.2 violet mediumpurple
6 2C2A35 9.8 violet very dark gray
7 886CBA 6.9 violet slateblue
8 44485B 6.7 blue-violet grayish purple
9 E4D4C9 2.9 orange lightgray
10 B6752A 2.4 orange chocolate

Color Families:

Family %
red-violet 34.3
violet 27.9
red-orange 14.1
red 11.7
blue-violet 6.7
orange 5.3

Texture Analysis

Metric Value
Global Roughness 0.141
Mean Local Roughness 0.012
Roughness Uniformity 0.017
Edge Density 0.039
Mean Gradient Magnitude 0.102
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.05
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.631
Spatial Variation 0.1
Texture Consistency 0.372

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.424
Brightness Variance 0.141
Brightness Uniformity 0.668
Brightness Skewness 0.406
Brightness Entropy 6.975
Rms Contrast 0.141
Michelson Contrast 1.0
Weber Contrast 0.614
Mean Local Contrast 0.014
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.467
Shadow Percentage 21.868
Midtone Percentage 74.51
Highlight Percentage 3.623
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.017
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.102
Contrast Clustering 0.628

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.795
Color Clustering 0.353
Color Transition Smoothness 0.733
Transition Uniformity 0.775
Sharp Transition Ratio 0.1
Transition Directionality 0.063
Mean Saturation 0.46
Saturation Variance 0.046
Low Saturation Ratio 0.206
Medium Saturation Ratio 0.563
High Saturation Ratio 0.231
Saturation Clustering 1.0
Hue Concentration 0.729
Complementary Balance 0.004
Analogous Dominance 0.638
Temperature Bias 0.206

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). C Minor - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0721.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-minor-research-on-harmony-variation-6_80m.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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