AQC0824

Nanopublication — Computational Image Analysis - AQC0824

Claim 1: Computational Image Analysis - AQC0824

Computational image analysis [3] of artwork D Minor [1] - Research on Harmony - Variation 7 (AQC0824) [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]: 2253x3004 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 C7C2B6 26.3 yellow-orange silver
2 CECAC1 20.0 yellow-orange lightgray
3 BFB4A3 14.5 yellow-orange steel gray
4 D9D8D3 10.7 white lightgrey
5 A6A29C 7.6 gray steel gray
6 CDB067 7.5 yellow-orange ochre
7 938D86 5.6 yellow-orange gray
8 D19830 3.6 yellow-orange goldenrod
9 726F6D 2.2 gray dimgray
10 393635 1.9 gray darkslategray
11 B57113 0.3 orange darkgoldenrod [Accent]
12 46425D 0.3 violet dusty mauve [Accent]

Color Families:

Family %
yellow-orange 77.6
gray 11.7
white 10.7
orange 0.3
violet 0.3

Accent Colors:

Hex Family Name Chroma
B57113 orange darkgoldenrod 60.4
46425D violet dusty mauve 17.0

Texture Analysis

Metric Value
Global Roughness 0.114
Mean Local Roughness 0.014
Roughness Uniformity 0.017
Edge Density 0.054
Mean Gradient Magnitude 0.114
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.041
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.619
Spatial Variation 0.063
Texture Consistency 0.478

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.723
Brightness Variance 0.114
Brightness Uniformity 0.843
Brightness Skewness -2.174
Brightness Entropy 6.439
Rms Contrast 0.114
Michelson Contrast 1.0
Weber Contrast 0.284
Mean Local Contrast 0.014
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.325
Shadow Percentage 1.907
Midtone Percentage 18.378
Highlight Percentage 79.714
Shadow Clipping 0.001
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.007
Medium Contrast 0.019
Coarse Contrast 0.03
Multiscale Contrast Ratio 0.248
Edge Contrast 0.114
Contrast Clustering 0.522

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.768
Color Clustering 0.271
Color Transition Smoothness 0.715
Transition Uniformity 0.793
Sharp Transition Ratio 0.1
Transition Directionality 0.053
Mean Saturation 0.14
Saturation Variance 0.032
Low Saturation Ratio 0.878
Medium Saturation Ratio 0.092
High Saturation Ratio 0.029
Saturation Clustering 1.0
Hue Concentration 0.971
Complementary Balance 0.005
Analogous Dominance 0.986
Temperature Bias 0.981

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). D Minor - Research on Harmony - Variation 7 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0824.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/d-minor-research-on-harmony-variation-7_94o.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)

831b5ceeaf795119af06053a1be95fe08f0f85f96de3cb1ffe8c593a8a601fdd