AQC0719 | NAN-COL000235

Nanopublication — Computational Image Analysis - AQC0719

B Minor - Research on Harmony - Variation 3

Claim 1: Computational Image Analysis - AQC0719

K-means clustering (10 colors) performed on artwork B Minor - Research on Harmony - Variation 3 (AQC0719) [1] by Arnaud Quercy [2] on 2025-10-03, according to IDS-CMP-2025 [3]. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

Context

Analysis performed according to IDS-CMP-2025 [3] includes four metric categories: (a) Color distribution via k-means (10 colors), (b) Texture analysis using Haralick features, (c) Brightness and contrast measurements, (d) Spatial pattern characterization. Source image: 3024x4032 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 74C497 16.7 yellow-green mediumaquamarine
2 62B589 15.4 yellow-green cadetblue
3 98DA95 11.8 yellow-green lightgreen
4 1C2423 11.7 gray very dark gray
5 AB8A46 11.4 yellow-orange peru
6 D2C4A6 11.3 yellow-orange tan
7 B3AD9D 9.7 yellow steel gray
8 3C434A 5.9 blue-violet grayish purple
9 747B7C 4.9 gray gray
10 3C9749 1.3 yellow-green seagreen
11 160A03 0.3 orange black [Accent]
12 1B0503 0.3 red-orange black [Accent]
13 B8C2CA 0.3 blue silver [Accent]
14 ADD4C8 0.3 green lightsteelblue [Accent]

Color Families:

Family %
yellow-green 45.1
yellow-orange 22.7
gray 16.6
yellow 9.7
blue-violet 5.9
orange 0.3
red-orange 0.3
blue 0.3
green 0.3

Accent Colors:

Hex Family Name Chroma
160A03 orange black 5.7
1B0503 red-orange black 8.9
B8C2CA blue silver 5.4
ADD4C8 green lightsteelblue 15.1

B) Texture Analysis

Metric Value
Global Roughness 0.204
Mean Local Roughness 0.036
Roughness Uniformity 0.029
Edge Density 0.178
Mean Gradient Magnitude 0.25
Gradient Variance 0.09
Gradient Smoothness 0.0
Directional Coherence 0.006
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.677
Spatial Variation 0.121
Texture Consistency 0.423

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.566
Brightness Variance 0.204
Brightness Uniformity 0.64
Brightness Skewness -1.121
Brightness Entropy 7.237
Rms Contrast 0.204
Michelson Contrast 1.0
Weber Contrast 0.764
Mean Local Contrast 0.036
Contrast Uniformity 0.133
Dynamic Range 1.0
Effective Dynamic Range 0.655
Shadow Percentage 16.911
Midtone Percentage 46.951
Highlight Percentage 36.138
Shadow Clipping 0.066
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.023
Medium Contrast 0.045
Coarse Contrast 0.055
Multiscale Contrast Ratio 0.41
Edge Contrast 0.25
Contrast Clustering 0.577

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.725
Color Clustering 0.775
Color Transition Smoothness 0.364
Transition Uniformity 0.373
Sharp Transition Ratio 0.1
Transition Directionality 0.008
Mean Saturation 0.359
Saturation Variance 0.029
Low Saturation Ratio 0.333
Medium Saturation Ratio 0.646
High Saturation Ratio 0.021
Saturation Clustering 0.997
Hue Concentration 0.603
Complementary Balance 0.085
Analogous Dominance 0.649
Temperature Bias -0.357

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 Ideamorphic Studies' computational imaging systems.

References

  1. [1] Quercy, A. (2024). B Minor - Research on Harmony - Variation 3 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0719.html
  2. [2] Quercy, A. (2025). ORCID https://orcid.org/0009-0000-2662-7790
  3. [3] Quercy, A. (2026). Computational Image Analysis Standard. https://ideamorphism.org/en/measurements/2025/09/ids-cmp-2025-computational-image-analysis-standard-5dq9.html

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

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