AQC0675

Nanopublication — Computational Image Analysis - AQC0675

Claim 1: Computational Image Analysis - AQC0675

Computational image analysis [3] of artwork Major [1] 2nd Interval - Reflexions 12 (AQC0675) [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]: 2303x3454 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D9BCBA 28.9 red-orange silver
2 E0CFD1 19.4 red lightgray
3 CBA9A3 12.6 red-orange tan
4 A58F8A 9.5 red-orange rosybrown
5 313237 7.7 gray dusty mauve
6 7F7474 7.2 gray gray
7 524F52 6.5 gray dusty mauve
8 D7A55D 2.9 yellow-orange sandybrown
9 DA8131 2.7 orange peru
10 A64F31 2.5 orange burnt sienna
11 17141C 0.3 violet black [Accent]
12 E5E7F6 0.3 blue-violet white [Accent]
13 161117 0.3 red-violet black [Accent]

Color Families:

Family %
red-orange 51.0
gray 21.4
red 19.4
orange 5.2
yellow-orange 2.9
violet 0.3
blue-violet 0.3
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
17141C violet black 7.2
E5E7F6 blue-violet white 8.2
161117 red-violet black 5.0

Texture Analysis

Metric Value
Global Roughness 0.199
Mean Local Roughness 0.015
Roughness Uniformity 0.02
Edge Density 0.057
Mean Gradient Magnitude 0.127
Gradient Variance 0.043
Gradient Smoothness 0.0
Directional Coherence 0.026
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.616
Spatial Variation 0.146
Texture Consistency 0.514

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.645
Brightness Variance 0.199
Brightness Uniformity 0.691
Brightness Skewness -1.054
Brightness Entropy 7.169
Rms Contrast 0.199
Michelson Contrast 1.0
Weber Contrast 0.646
Mean Local Contrast 0.016
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.635
Shadow Percentage 12.074
Midtone Percentage 26.382
Highlight Percentage 61.544
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.009
Medium Contrast 0.021
Coarse Contrast 0.034
Multiscale Contrast Ratio 0.252
Edge Contrast 0.127
Contrast Clustering 0.486

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.734
Color Clustering 0.642
Color Transition Smoothness 0.667
Transition Uniformity 0.71
Sharp Transition Ratio 0.1
Transition Directionality 0.029
Mean Saturation 0.189
Saturation Variance 0.03
Low Saturation Ratio 0.869
Medium Saturation Ratio 0.09
High Saturation Ratio 0.041
Saturation Clustering 1.0
Hue Concentration 0.726
Complementary Balance 0.127
Analogous Dominance 0.864
Temperature Bias 0.737

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). Major 2nd Interval - Reflexions 12 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0675.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/major-2nd-interval-reflexions-12_7iq.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)

19b94d9d4262f4925e3d6f1df2a0f58e166e909e6df59f2dbddf55d3d80184d9