AQC0558

Nanopublication — Computational Image Analysis - AQC0558

by Arnaud Quercy · C Major9 - Research on Harmony - Variation 10 · 2024

Claim 1: Computational Image Analysis - AQC0558

Analysis record [3]: C Major9 - Research [1] on Harmony - Variation 10 (AQC0558) [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 0E0E19 18.6 violet black
2 CB5D2E 16.0 orange chocolate
3 DAA78E 12.5 orange tan
4 BE8D77 11.0 orange rosybrown
5 25242E 10.4 violet very dark gray
6 B74A1C 9.4 orange burnt sienna
7 DF7042 8.1 orange peru
8 DDCFC1 6.2 yellow-orange lightgray
9 BFB2A6 5.2 orange steel gray
10 544C4F 2.6 gray dusty mauve
11 F6F5EA 0.3 yellow-green white [Accent]

Color Families:

Family %
orange 62.2
violet 29.0
yellow-orange 6.2
gray 2.6
yellow-green 0.3

Accent Colors:

Hex Family Name Chroma
F6F5EA yellow-green white 5.4

Texture Analysis

Metric Value
Global Roughness 0.251
Mean Local Roughness 0.018
Roughness Uniformity 0.014
Edge Density 0.103
Mean Gradient Magnitude 0.183
Gradient Variance 0.03
Gradient Smoothness 0.057
Directional Coherence 0.005
Pattern Complexity 0.111
Pattern Repetition 1.0
Detail Frequency Ratio 0.6
Spatial Variation 0.215
Texture Consistency 0.414

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.436
Brightness Variance 0.251
Brightness Uniformity 0.424
Brightness Skewness -0.27
Brightness Entropy 7.538
Rms Contrast 0.251
Michelson Contrast 1.0
Weber Contrast 0.915
Mean Local Contrast 0.021
Contrast Uniformity 0.321
Dynamic Range 1.0
Effective Dynamic Range 0.745
Shadow Percentage 31.092
Midtone Percentage 47.2
Highlight Percentage 21.708
Shadow Clipping 0.041
Highlight Clipping 0.001
Tonal Balance 0.236
Fine Contrast 0.01
Medium Contrast 0.027
Coarse Contrast 0.051
Multiscale Contrast Ratio 0.193
Edge Contrast 0.183
Contrast Clustering 0.586

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.741
Color Clustering 0.741
Color Transition Smoothness 0.532
Transition Uniformity 0.787
Sharp Transition Ratio 0.1
Transition Directionality 0.004
Mean Saturation 0.477
Saturation Variance 0.064
Low Saturation Ratio 0.247
Medium Saturation Ratio 0.435
High Saturation Ratio 0.318
Saturation Clustering 0.998
Hue Concentration 0.533
Complementary Balance 0.001
Analogous Dominance 0.7
Temperature Bias 0.622

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 Major9 - Research on Harmony - Variation 10 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0558.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-major9-research-on-harmony-variation-10_698.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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