AQC0539 | NAN-COL000396

Nanopublication — Computational Image Analysis - AQC0539

Ab Major 9 - Research on Harmony - Variation 7

Claim 1: Computational Image Analysis - AQC0539

The artwork Ab Major 9 - Research on Harmony - Variation 7 (AQC0539) [1] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2025-10-03. Method: k-means clustering with 10 colors extracted. Metrics documented: color distribution, texture analysis, brightness/contrast, spatial patterns.

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: 2132x2843 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 DA626C 21.6 red-orange indianred
2 B85059 16.7 red-orange burnt sienna
3 152258 16.2 violet very dark purple
4 100B1B 10.4 violet very dark gray
5 E87986 8.8 red-orange lightcoral
6 0B2976 8.0 violet indigo
7 3E4462 7.0 violet dusty mauve
8 68718E 3.9 blue-violet grayish purple
9 86403B 3.8 red-orange burnt sienna
10 D9CDCB 3.6 white lightgray
11 EFE9E1 0.3 yellow-orange white [Accent]
12 AD6C37 0.3 orange burnt sienna [Accent]
13 4A3539 0.3 red darkslategray [Accent]
14 F8F5EB 0.3 yellow white [Accent]
15 76566C 0.3 red-violet dusty mauve [Accent]

Color Families:

Family %
red-orange 50.9
violet 41.6
blue-violet 3.9
white 3.6
yellow-orange 0.3
orange 0.3
red 0.3
yellow 0.3
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
EFE9E1 yellow-orange white 5.1
AD6C37 orange burnt sienna 45.2
4A3539 red darkslategray 10.0
F8F5EB yellow white 5.1
76566C red-violet dusty mauve 18.4

B) Texture Analysis

Metric Value
Global Roughness 0.208
Mean Local Roughness 0.032
Roughness Uniformity 0.028
Edge Density 0.183
Mean Gradient Magnitude 0.245
Gradient Variance 0.075
Gradient Smoothness 0.0
Directional Coherence 0.025
Pattern Complexity 0.122
Pattern Repetition 1.0
Detail Frequency Ratio 0.668
Spatial Variation 0.136
Texture Consistency 0.557

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.364
Brightness Variance 0.208
Brightness Uniformity 0.428
Brightness Skewness 0.091
Brightness Entropy 7.349
Rms Contrast 0.208
Michelson Contrast 1.0
Weber Contrast 0.841
Mean Local Contrast 0.033
Contrast Uniformity 0.213
Dynamic Range 1.0
Effective Dynamic Range 0.608
Shadow Percentage 42.242
Midtone Percentage 53.182
Highlight Percentage 4.577
Shadow Clipping 0.001
Highlight Clipping 0.006
Tonal Balance 0.049
Fine Contrast 0.017
Medium Contrast 0.041
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.245
Contrast Clustering 0.443

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.721
Color Clustering 0.68
Color Transition Smoothness 0.368
Transition Uniformity 0.492
Sharp Transition Ratio 0.1
Transition Directionality 0.028
Mean Saturation 0.577
Saturation Variance 0.039
Low Saturation Ratio 0.082
Medium Saturation Ratio 0.691
High Saturation Ratio 0.227
Saturation Clustering 0.998
Hue Concentration 0.475
Complementary Balance 0.007
Analogous Dominance 0.551
Temperature Bias 0.2

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). Ab Major 9 - Research on Harmony - Variation 7 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0539.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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