AQC0862 | NAN-COL000007

Nanopublication — Computational Image Analysis - AQC0862

F# Major - Research on Harmony - Variation 6

Claim 1: Computational Image Analysis - AQC0862

K-means clustering (10 colors) performed on artwork F# Major - Research on Harmony - Variation 6 (AQC0862) [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: 2476x3302 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 D6D2BF 25.2 yellow lightgray
2 D9DBD9 14.4 white gainsboro
3 C0C9CE 13.3 white silver
4 B9BEA5 8.6 yellow-green steel gray
5 6E9DAC 7.9 blue cadetblue
6 4B8490 7.8 blue-green steelblue
7 A1B2BE 7.0 blue steel gray
8 8E6EA1 6.2 red-violet dusty mauve
9 693764 5.9 red-violet dusty mauve
10 282A31 3.8 blue-violet very dark gray
11 CE9C89 0.3 orange rosybrown [Accent]
12 BD877A 0.3 red-orange rosybrown [Accent]
13 236C69 0.3 green seagreen [Accent]
14 666285 0.3 violet dusty mauve [Accent]

Color Families:

Family %
white 27.6
yellow 25.2
blue 14.9
red-violet 12.0
yellow-green 8.6
blue-green 7.8
blue-violet 3.8
orange 0.3
red-orange 0.3
green 0.3
violet 0.3

Accent Colors:

Hex Family Name Chroma
CE9C89 orange rosybrown 23.3
BD877A red-orange rosybrown 24.2
236C69 green seagreen 23.5
666285 violet dusty mauve 21.5

B) Texture Analysis

Metric Value
Global Roughness 0.196
Mean Local Roughness 0.013
Roughness Uniformity 0.016
Edge Density 0.051
Mean Gradient Magnitude 0.119
Gradient Variance 0.03
Gradient Smoothness 0.0
Directional Coherence 0.027
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.599
Spatial Variation 0.114
Texture Consistency 0.585

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.68
Brightness Variance 0.196
Brightness Uniformity 0.712
Brightness Skewness -1.155
Brightness Entropy 7.055
Rms Contrast 0.196
Michelson Contrast 1.0
Weber Contrast 0.55
Mean Local Contrast 0.015
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.612
Shadow Percentage 8.189
Midtone Percentage 25.827
Highlight Percentage 65.984
Shadow Clipping 0.002
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.007
Medium Contrast 0.018
Coarse Contrast 0.032
Multiscale Contrast Ratio 0.218
Edge Contrast 0.119
Contrast Clustering 0.415

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.742
Color Clustering 0.783
Color Transition Smoothness 0.697
Transition Uniformity 0.794
Sharp Transition Ratio 0.1
Transition Directionality 0.032
Mean Saturation 0.2
Saturation Variance 0.028
Low Saturation Ratio 0.737
Medium Saturation Ratio 0.26
High Saturation Ratio 0.003
Saturation Clustering 1.0
Hue Concentration 0.537
Complementary Balance 0.09
Analogous Dominance 0.551
Temperature Bias -0.4

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. (2025). F# Major - Research on Harmony - Variation 6 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0862.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/2025/11/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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