AQC0548

Nanopublication — Computational Image Analysis - AQC0548

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

Claim 1: Computational Image Analysis - AQC0548

K-means clustering analysis [3] (10 colors) performed on artwork C Major9 - Research [1] on Harmony (AQC0548) [2] by Arnaud Quercy [2] on 2026-02-04. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

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 CC6029 15.7 orange chocolate
2 DC6F39 14.1 orange peru
3 E09873 13.6 orange darksalmon
4 272424 13.3 gray very dark gray
5 CA8460 12.6 orange indianred
6 151010 10.7 black black
7 B84F1A 8.7 orange burnt sienna
8 EF854F 6.2 orange coral
9 4B4242 3.2 gray darkslategray
10 DACCB3 1.9 yellow-orange silver
11 F6F3DE 0.3 yellow beige [Accent]
12 7E534A 0.3 red-orange dimgray [Accent]

Color Families:

Family %
orange 70.9
gray 16.5
black 10.7
yellow-orange 1.9
yellow 0.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
F6F3DE yellow beige 10.4
7E534A red-orange dimgray 21.4

Texture Analysis

Metric Value
Global Roughness 0.21
Mean Local Roughness 0.029
Roughness Uniformity 0.017
Edge Density 0.194
Mean Gradient Magnitude 0.243
Gradient Variance 0.04
Gradient Smoothness 0.174
Directional Coherence 0.012
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.649
Spatial Variation 0.165
Texture Consistency 0.335

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.442
Brightness Variance 0.21
Brightness Uniformity 0.525
Brightness Skewness -0.605
Brightness Entropy 7.273
Rms Contrast 0.21
Michelson Contrast 1.0
Weber Contrast 0.84
Mean Local Contrast 0.032
Contrast Uniformity 0.449
Dynamic Range 1.0
Effective Dynamic Range 0.616
Shadow Percentage 26.911
Midtone Percentage 63.898
Highlight Percentage 9.191
Shadow Clipping 0.044
Highlight Clipping 0.0
Tonal Balance 0.013
Fine Contrast 0.016
Medium Contrast 0.04
Coarse Contrast 0.059
Multiscale Contrast Ratio 0.275
Edge Contrast 0.243
Contrast Clustering 0.665

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.766
Color Clustering 0.548
Color Transition Smoothness 0.391
Transition Uniformity 0.75
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.525
Saturation Variance 0.08
Low Saturation Ratio 0.246
Medium Saturation Ratio 0.366
High Saturation Ratio 0.388
Saturation Clustering 0.998
Hue Concentration 0.991
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0548.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-major9-research-on-harmony_65c.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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