AQC0414

Nanopublication — Computational Image Analysis - AQC0414

Claim 1: Computational Image Analysis - AQC0414

K-means clustering analysis [3] (10 colors) performed on artwork The [1] man and his moustache (AQC0414) [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]: 1540x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 2F280E 21.5 yellow-orange very dark green
2 D2C6AF 12.1 yellow-orange silver
3 CB9572 11.5 orange darksalmon
4 703C29 9.8 orange russet
5 B68B35 9.0 yellow-orange peru
6 AB5134 8.9 red-orange burnt sienna
7 27456A 8.9 blue-violet grayish purple
8 7FA5BD 8.3 blue cadetblue
9 416F9A 5.6 blue-violet grayish purple
10 7B7461 4.3 yellow dimgray
11 082765 0.3 violet very dark purple [Accent]
12 595A48 0.3 yellow-green dark brown [Accent]
13 A1798C 0.3 red dusty mauve [Accent]

Color Families:

Family %
yellow-orange 42.6
orange 21.3
blue-violet 14.5
red-orange 8.9
blue 8.3
yellow 4.3
violet 0.3
yellow-green 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
082765 violet very dark purple 42.2
595A48 yellow-green dark brown 10.8
A1798C red dusty mauve 19.4

Texture Analysis

Metric Value
Global Roughness 0.219
Mean Local Roughness 0.019
Roughness Uniformity 0.017
Edge Density 0.083
Mean Gradient Magnitude 0.151
Gradient Variance 0.033
Gradient Smoothness 0.0
Directional Coherence 0.035
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.614
Spatial Variation 0.109
Texture Consistency 0.765

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.433
Brightness Variance 0.219
Brightness Uniformity 0.495
Brightness Skewness 0.189
Brightness Entropy 7.592
Rms Contrast 0.219
Michelson Contrast 1.0
Weber Contrast 0.799
Mean Local Contrast 0.02
Contrast Uniformity 0.182
Dynamic Range 1.0
Effective Dynamic Range 0.659
Shadow Percentage 39.193
Midtone Percentage 42.779
Highlight Percentage 18.028
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.32
Fine Contrast 0.01
Medium Contrast 0.025
Coarse Contrast 0.034
Multiscale Contrast Ratio 0.294
Edge Contrast 0.151
Contrast Clustering 0.235

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.673
Color Clustering 0.685
Color Transition Smoothness 0.596
Transition Uniformity 0.778
Sharp Transition Ratio 0.1
Transition Directionality 0.041
Mean Saturation 0.527
Saturation Variance 0.061
Low Saturation Ratio 0.21
Medium Saturation Ratio 0.47
High Saturation Ratio 0.32
Saturation Clustering 0.999
Hue Concentration 0.483
Complementary Balance 0.15
Analogous Dominance 0.758
Temperature Bias 0.507

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 (2023). The man and his moustache — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0414.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/the-man-and-his-moustache_4p8.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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