AQC0527 | NAN-COL000408

Nanopublication — Computational Image Analysis - AQC0527

D Major9 - Research on Harmony - Variation 7

Claim 1: Computational Image Analysis - AQC0527

K-means clustering (10 colors) performed on artwork D Major9 - Research on Harmony - Variation 7 (AQC0527) [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: 2683x3685 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 D2A326 15.2 yellow-orange goldenrod
2 33312D 15.1 gray darkslategray
3 9A9C64 12.0 yellow ochre
4 B0732E 11.3 orange burnt sienna
5 E3B53B 10.7 yellow-orange sandybrown
6 B5B077 9.7 yellow ochre
7 7A7469 9.5 yellow-orange dimgray
8 E1CAA2 7.6 yellow-orange burlywood
9 5D554B 6.3 orange dark brown
10 E5E7DF 2.6 white white
11 79B672 0.3 yellow-green darkseagreen [Accent]

Color Families:

Family %
yellow-orange 43.1
yellow 21.6
orange 17.6
gray 15.1
white 2.6
yellow-green 0.3

Accent Colors:

Hex Family Name Chroma
79B672 yellow-green darkseagreen 43.9

B) Texture Analysis

Metric Value
Global Roughness 0.195
Mean Local Roughness 0.018
Roughness Uniformity 0.019
Edge Density 0.075
Mean Gradient Magnitude 0.158
Gradient Variance 0.04
Gradient Smoothness 0.0
Directional Coherence 0.005
Pattern Complexity 0.108
Pattern Repetition 1.0
Detail Frequency Ratio 0.623
Spatial Variation 0.13
Texture Consistency 0.547

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.544
Brightness Variance 0.195
Brightness Uniformity 0.641
Brightness Skewness -0.475
Brightness Entropy 7.359
Rms Contrast 0.195
Michelson Contrast 1.0
Weber Contrast 0.732
Mean Local Contrast 0.02
Contrast Uniformity 0.054
Dynamic Range 1.0
Effective Dynamic Range 0.643
Shadow Percentage 17.205
Midtone Percentage 53.691
Highlight Percentage 29.104
Shadow Clipping 0.001
Highlight Clipping 0.021
Tonal Balance 0.043
Fine Contrast 0.009
Medium Contrast 0.025
Coarse Contrast 0.043
Multiscale Contrast Ratio 0.213
Edge Contrast 0.158
Contrast Clustering 0.453

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.727
Color Clustering 0.646
Color Transition Smoothness 0.601
Transition Uniformity 0.748
Sharp Transition Ratio 0.1
Transition Directionality 0.009
Mean Saturation 0.432
Saturation Variance 0.084
Low Saturation Ratio 0.384
Medium Saturation Ratio 0.299
High Saturation Ratio 0.317
Saturation Clustering 1.0
Hue Concentration 0.97
Complementary Balance 0.0
Analogous Dominance 0.992
Temperature Bias 0.884

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). D Major9 - Research on Harmony - Variation 7 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0527.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

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