AQC0760

Nanopublication — Computational Image Analysis - AQC0760

Claim 1: Computational Image Analysis - AQC0760

Computational image analysis [3] of artwork F Minor [1] - Research on Harmony - Variation 13 (AQC0760) [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]: 2975x3967 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 32272B 22.1 red very dark gray
2 5AA0E6 20.0 blue-violet cornflowerblue
3 7B4D66 11.5 red dusty mauve
4 75578D 11.2 violet dusty mauve
5 886AA2 10.8 violet dusty mauve
6 76AEE9 10.1 blue-violet skyblue
7 554548 7.9 red darkslategray
8 D93E27 2.4 red-orange chocolate
9 EBAB95 2.3 orange burlywood
10 373375 1.8 violet darkslateblue
11 B58F49 0.3 yellow-orange peru [Accent]
12 98C8E7 0.3 blue skyblue [Accent]

Color Families:

Family %
red 41.5
blue-violet 30.1
violet 23.7
red-orange 2.4
orange 2.3
yellow-orange 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
B58F49 yellow-orange peru 42.4
98C8E7 blue skyblue 21.5

Texture Analysis

Metric Value
Global Roughness 0.173
Mean Local Roughness 0.009
Roughness Uniformity 0.011
Edge Density 0.025
Mean Gradient Magnitude 0.096
Gradient Variance 0.021
Gradient Smoothness 0.0
Directional Coherence 0.032
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.579
Spatial Variation 0.123
Texture Consistency 0.416

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.413
Brightness Variance 0.173
Brightness Uniformity 0.58
Brightness Skewness -0.048
Brightness Entropy 7.129
Rms Contrast 0.173
Michelson Contrast 1.0
Weber Contrast 0.738
Mean Local Contrast 0.012
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.51
Shadow Percentage 31.729
Midtone Percentage 64.02
Highlight Percentage 4.252
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.014
Coarse Contrast 0.028
Multiscale Contrast Ratio 0.162
Edge Contrast 0.096
Contrast Clustering 0.584

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.785
Color Clustering 0.47
Color Transition Smoothness 0.741
Transition Uniformity 0.855
Sharp Transition Ratio 0.1
Transition Directionality 0.042
Mean Saturation 0.401
Saturation Variance 0.029
Low Saturation Ratio 0.319
Medium Saturation Ratio 0.653
High Saturation Ratio 0.028
Saturation Clustering 1.0
Hue Concentration 0.551
Complementary Balance 0.008
Analogous Dominance 0.586
Temperature Bias 0.004

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). F Minor - Research on Harmony - Variation 13 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0760.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/f-minor-research-on-harmony-variation-13_8fs.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)

74aa207374d0272927a0d94cfc0768d78b1afc78d0c2db2688c673cc789b9d44