AQC0782

Nanopublication — Computational Image Analysis - AQC0782

Claim 1: Computational Image Analysis - AQC0782

Computational image analysis [3] of artwork Eb Major [1] - Research on Harmony - Variation 4 (AQC0782) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 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]: 2292x3438 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 C45F12 16.2 orange chocolate
2 2F2B3F 13.6 violet very dark gray
3 B7AEA0 13.0 yellow-orange steel gray
4 161116 11.6 black black
5 5D4767 10.2 red-violet dusty mauve
6 A95E3B 9.3 orange burnt sienna
7 CFC4C0 8.7 white silver
8 CF7A54 6.5 orange peru
9 6E598E 6.3 violet dusty mauve
10 9B83C6 4.6 violet mediumpurple
11 430500 0.3 red-orange very dark red [Accent]
12 F8F2E1 0.3 yellow white [Accent]
13 9E6572 0.3 red gray [Accent]

Color Families:

Family %
orange 31.9
violet 24.5
yellow-orange 13.0
black 11.6
red-violet 10.2
white 8.7
red-orange 0.3
yellow 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
430500 red-orange very dark red 33.3
F8F2E1 yellow white 9.1
9E6572 red gray 25.1

Texture Analysis

Metric Value
Global Roughness 0.218
Mean Local Roughness 0.016
Roughness Uniformity 0.015
Edge Density 0.092
Mean Gradient Magnitude 0.168
Gradient Variance 0.042
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.114
Pattern Repetition 1.0
Detail Frequency Ratio 0.575
Spatial Variation 0.139
Texture Consistency 0.673

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.428
Brightness Variance 0.218
Brightness Uniformity 0.49
Brightness Skewness -0.035
Brightness Entropy 7.617
Rms Contrast 0.218
Michelson Contrast 1.0
Weber Contrast 0.85
Mean Local Contrast 0.021
Contrast Uniformity 0.101
Dynamic Range 1.0
Effective Dynamic Range 0.706
Shadow Percentage 32.257
Midtone Percentage 48.889
Highlight Percentage 18.855
Shadow Clipping 0.003
Highlight Clipping 0.001
Tonal Balance 0.344
Fine Contrast 0.008
Medium Contrast 0.025
Coarse Contrast 0.048
Multiscale Contrast Ratio 0.164
Edge Contrast 0.168
Contrast Clustering 0.327

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.716
Color Clustering 0.65
Color Transition Smoothness 0.56
Transition Uniformity 0.707
Sharp Transition Ratio 0.1
Transition Directionality 0.019
Mean Saturation 0.432
Saturation Variance 0.077
Low Saturation Ratio 0.358
Medium Saturation Ratio 0.442
High Saturation Ratio 0.199
Saturation Clustering 0.999
Hue Concentration 0.516
Complementary Balance 0.008
Analogous Dominance 0.525
Temperature Bias 0.449

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). Eb Major - Research on Harmony - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0782.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/eb-major-research-on-harmony-variation-4_8oc.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)

440d11c0235f0ee291ce1a6f217acef2935f4ab3f16f9461e3c7b3d20761adb1