AQC1075 | NAN-COL000638

Nanopublication — Computational Image Analysis - AQC1075

Watercolor Study in F# Minor No. 1

Claim 1: Computational Image Analysis - AQC1075

K-means clustering (10 colors) performed on artwork Watercolor Study in F# Minor No. 1 (AQC1075) [1] by Arnaud Quercy [2] on 2026-07-13, 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: 1527x2036 pixels. Analysis date: 2026-07-13.

A) Color Analysis

Rank Color Hex % Family Name
1 89A88B 25.3 yellow-green darkseagreen
2 789B80 21.5 yellow-green gray
3 C8B28D 12.3 yellow-orange tan
4 598171 8.5 green dimgray
5 766B5A 7.3 yellow-orange dimgrey
6 9DB4A7 6.8 yellow-green steel gray
7 8E8172 6.8 yellow-orange grey
8 090706 6.1 black black
9 63561A 3.6 yellow-orange dark brown
10 3A3B35 1.8 gray darkslategray
11 3B0315 0.3 red very dark red [Accent]
12 582A03 0.3 orange maroon [Accent]
13 7284A3 0.3 blue-violet grayish purple [Accent]
14 898431 0.3 yellow olivedrab [Accent]

Color Families:

Family %
yellow-green 53.7
yellow-orange 30.0
green 8.5
black 6.1
gray 1.8
red 0.3
orange 0.3
blue-violet 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
3B0315 red very dark red 28.3
582A03 orange maroon 36.7
7284A3 blue-violet grayish purple 19.0
898431 yellow olivedrab 44.9

B) Texture Analysis

Metric Value
Global Roughness 0.167
Mean Local Roughness 0.023
Roughness Uniformity 0.02
Edge Density 0.086
Mean Gradient Magnitude 0.174
Gradient Variance 0.056
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.137
Pattern Repetition 1.0
Detail Frequency Ratio 0.626
Spatial Variation 0.066
Texture Consistency 0.412

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.53
Brightness Variance 0.167
Brightness Uniformity 0.684
Brightness Skewness -1.624
Brightness Entropy 6.892
Rms Contrast 0.167
Michelson Contrast 1.0
Weber Contrast 0.514
Mean Local Contrast 0.024
Contrast Uniformity 0.119
Dynamic Range 1.0
Effective Dynamic Range 0.659
Shadow Percentage 9.673
Midtone Percentage 74.351
Highlight Percentage 15.975
Shadow Clipping 0.127
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.014
Medium Contrast 0.03
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.174
Contrast Clustering 0.588

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.742
Color Clustering 0.788
Color Transition Smoothness 0.552
Transition Uniformity 0.587
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.261
Saturation Variance 0.027
Low Saturation Ratio 0.777
Medium Saturation Ratio 0.178
High Saturation Ratio 0.045
Saturation Clustering 0.996
Hue Concentration 0.597
Complementary Balance 0.039
Analogous Dominance 0.557
Temperature Bias -0.095

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. (2026). Watercolor Study in F# Minor No. 1 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1075.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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