AQC0855

Nanopublication — Computational Image Analysis - AQC0855

by Arnaud Quercy · Db Major - Research on Harmony - Variation 12 · 2025

Claim 1: Computational Image Analysis - AQC0855

K-means clustering analysis [3] (10 colors) performed on artwork Db Major [1] - Research on Harmony - Variation 12 (AQC0855) [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]: 2239x2986 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E3E0D7 28.2 yellow gainsboro
2 CED5D4 20.3 white lightgray
3 BBC5C0 12.9 white silver
4 98B1B5 7.9 blue-green steel gray
5 78969F 7.2 blue lightslategray
6 9E6187 6.4 red-violet dusty mauve
7 5A7585 5.2 blue blue gray
8 465559 4.5 blue-green darkslategray
9 2B2A2F 4.2 gray very dark gray
10 753767 3.1 red-violet dusty mauve
11 D3AC8A 0.3 orange tan [Accent]
12 325485 0.3 blue-violet grayish purple [Accent]

Color Families:

Family %
white 33.2
yellow 28.2
blue-green 12.5
blue 12.4
red-violet 9.6
gray 4.2
orange 0.3
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
D3AC8A orange tan 24.7
325485 blue-violet grayish purple 31.3

Texture Analysis

Metric Value
Global Roughness 0.213
Mean Local Roughness 0.015
Roughness Uniformity 0.019
Edge Density 0.062
Mean Gradient Magnitude 0.128
Gradient Variance 0.044
Gradient Smoothness 0.0
Directional Coherence 0.037
Pattern Complexity 0.113
Pattern Repetition 1.0
Detail Frequency Ratio 0.606
Spatial Variation 0.123
Texture Consistency 0.613

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.692
Brightness Variance 0.213
Brightness Uniformity 0.692
Brightness Skewness -1.013
Brightness Entropy 7.116
Rms Contrast 0.213
Michelson Contrast 1.0
Weber Contrast 0.611
Mean Local Contrast 0.016
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.631
Shadow Percentage 9.054
Midtone Percentage 25.135
Highlight Percentage 65.81
Shadow Clipping 0.003
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.021
Coarse Contrast 0.034
Multiscale Contrast Ratio 0.234
Edge Contrast 0.128
Contrast Clustering 0.387

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.728
Color Clustering 0.881
Color Transition Smoothness 0.671
Transition Uniformity 0.7
Sharp Transition Ratio 0.1
Transition Directionality 0.048
Mean Saturation 0.145
Saturation Variance 0.021
Low Saturation Ratio 0.842
Medium Saturation Ratio 0.157
High Saturation Ratio 0.001
Saturation Clustering 1.0
Hue Concentration 0.443
Complementary Balance 0.04
Analogous Dominance 0.573
Temperature Bias -0.164

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 (2025). Db Major - Research on Harmony - Variation 12 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0855.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/db-major-research-on-harmony-variation-12_9gq.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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