AQC1111

Nanopublication — Computational Image Analysis - AQC1111

D7 - Research on Harmony - Variations 3

Claim 1: Computational Image Analysis - AQC1111

K-means clustering (10 colors) performed on artwork D7 - Research on Harmony - Variations 3 (AQC1111) [1] by Arnaud Quercy [2] on 2026-10-02, 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: 2026-10-02.

A) Color Analysis

Rank Color Hex % Family Name
1 BCB3A4 33.0 yellow-orange steel gray
2 AEA595 15.3 yellow-orange steel gray
3 9F6A50 12.1 orange burnt sienna
4 918B78 9.2 yellow gray
5 814227 6.6 orange russet
6 271B0F 6.4 orange very dark gray
7 DCD7CB 5.4 yellow-orange lightgray
8 AA3A07 4.8 orange russet
9 B75F29 4.3 orange burnt sienna
10 2E332C 2.9 yellow-green darkslategray
11 582B1F 0.3 red-orange russet [Accent]

Color Families:

Family %
yellow-orange 53.7
orange 34.2
yellow 9.2
yellow-green 2.9
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
582B1F red-orange russet 26.2

B) Texture Analysis

Metric Value
Global Roughness 0.194
Mean Local Roughness 0.015
Roughness Uniformity 0.009
Edge Density 0.02
Mean Gradient Magnitude 0.101
Gradient Variance 0.013
Gradient Smoothness 0.0
Directional Coherence 0.013
Pattern Complexity 0.137
Pattern Repetition 1.0
Detail Frequency Ratio 0.646
Spatial Variation 0.123
Texture Consistency 0.71

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.556
Brightness Variance 0.194
Brightness Uniformity 0.651
Brightness Skewness -0.811
Brightness Entropy 7.078
Rms Contrast 0.194
Michelson Contrast 1.0
Weber Contrast 0.622
Mean Local Contrast 0.014
Contrast Uniformity 0.306
Dynamic Range 0.988
Effective Dynamic Range 0.671
Shadow Percentage 15.973
Midtone Percentage 40.304
Highlight Percentage 43.723
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.018
Coarse Contrast 0.023
Multiscale Contrast Ratio 0.464
Edge Contrast 0.101
Contrast Clustering 0.29

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.751
Color Clustering 0.678
Color Transition Smoothness 0.74
Transition Uniformity 0.904
Sharp Transition Ratio 0.1
Transition Directionality 0.013
Mean Saturation 0.312
Saturation Variance 0.073
Low Saturation Ratio 0.667
Medium Saturation Ratio 0.184
High Saturation Ratio 0.148
Saturation Clustering 0.999
Hue Concentration 0.934
Complementary Balance 0.001
Analogous Dominance 0.968
Temperature Bias 0.936

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). D7 - Research on Harmony - Variations 3 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1111.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

Where this work lives

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

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