AQC0664

Nanopublication — Computational Image Analysis - AQC0664

Claim 1: Computational Image Analysis - AQC0664

The artwork C+ - Research [1] on Harmony (AQC0664) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-02-04. Method: k-means clustering with 10 colors extracted. Metrics documented: color distribution, texture analysis, brightness/contrast, spatial patterns.

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]: 2384x3178 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 EE693A 18.6 orange tomato
2 AAB1AF 14.7 gray steel gray
3 EA8159 14.5 orange coral
4 C8C8C3 12.3 white silver
5 8B9797 11.4 gray lightslategray
6 707675 8.8 gray dimgray
7 51514F 8.3 gray darkslategray
8 EB9774 6.3 orange darksalmon
9 B75844 2.6 red-orange indianred
10 372019 2.5 red-orange very dark gray
11 F2E2E4 0.3 red white [Accent]
12 2D3A3D 0.3 blue-green darkslategray [Accent]
13 2D393C 0.3 blue darkslategray [Accent]

Color Families:

Family %
gray 43.2
orange 39.4
white 12.3
red-orange 5.1
red 0.3
blue-green 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
F2E2E4 red white 6.1
2D3A3D blue-green darkslategray 5.0
2D393C blue darkslategray 5.7

Texture Analysis

Metric Value
Global Roughness 0.145
Mean Local Roughness 0.017
Roughness Uniformity 0.015
Edge Density 0.092
Mean Gradient Magnitude 0.149
Gradient Variance 0.029
Gradient Smoothness 0.0
Directional Coherence 0.01
Pattern Complexity 0.124
Pattern Repetition 1.0
Detail Frequency Ratio 0.607
Spatial Variation 0.093
Texture Consistency 0.617

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.58
Brightness Variance 0.145
Brightness Uniformity 0.749
Brightness Skewness -0.819
Brightness Entropy 7.115
Rms Contrast 0.145
Michelson Contrast 1.0
Weber Contrast 0.51
Mean Local Contrast 0.019
Contrast Uniformity 0.179
Dynamic Range 1.0
Effective Dynamic Range 0.494
Shadow Percentage 7.397
Midtone Percentage 65.305
Highlight Percentage 27.298
Shadow Clipping 0.002
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.009
Medium Contrast 0.023
Coarse Contrast 0.038
Multiscale Contrast Ratio 0.234
Edge Contrast 0.149
Contrast Clustering 0.383

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.742
Color Clustering 0.616
Color Transition Smoothness 0.621
Transition Uniformity 0.803
Sharp Transition Ratio 0.1
Transition Directionality 0.024
Mean Saturation 0.345
Saturation Variance 0.086
Low Saturation Ratio 0.553
Medium Saturation Ratio 0.255
High Saturation Ratio 0.192
Saturation Clustering 1.0
Hue Concentration 0.827
Complementary Balance 0.085
Analogous Dominance 0.915
Temperature Bias 0.83

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+ - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0664.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-research-on-harmony_7eg.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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