AQC1144

Nanopublication — Computational Image Analysis - AQC1144

Bb Major - Research on Harmony - Variations 20

Claim 1: Computational Image Analysis - AQC1144

Analysis record: Bb Major - Research on Harmony - Variations 20 (AQC1144) [1] by Arnaud Quercy [2], per IDS-CMP-2025 [3]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-10-02.

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 D1C4B0 36.1 yellow-orange silver
2 BEB09A 16.6 yellow-orange tan
3 894356 10.7 red burnt sienna
4 9F8295 7.6 red-violet dusty mauve
5 4B1835 7.5 red very dark red
6 837676 7.0 red-orange gray
7 602D49 5.5 red dusty mauve
8 211A19 4.5 gray very dark gray
9 D07842 3.0 orange peru
10 BE4D05 1.4 orange chocolate

Color Families:

Family %
yellow-orange 52.7
red 23.7
red-violet 7.6
red-orange 7.0
gray 4.5
orange 4.4

B) Texture Analysis

Metric Value
Global Roughness 0.228
Mean Local Roughness 0.017
Roughness Uniformity 0.016
Edge Density 0.067
Mean Gradient Magnitude 0.119
Gradient Variance 0.028
Gradient Smoothness 0.0
Directional Coherence 0.038
Pattern Complexity 0.132
Pattern Repetition 1.0
Detail Frequency Ratio 0.655
Spatial Variation 0.138
Texture Consistency 0.739

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.565
Brightness Variance 0.228
Brightness Uniformity 0.596
Brightness Skewness -0.661
Brightness Entropy 7.012
Rms Contrast 0.228
Michelson Contrast 1.0
Weber Contrast 0.761
Mean Local Contrast 0.017
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.655
Shadow Percentage 19.88
Midtone Percentage 28.988
Highlight Percentage 51.133
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.021
Coarse Contrast 0.026
Multiscale Contrast Ratio 0.4
Edge Contrast 0.119
Contrast Clustering 0.261

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.767
Color Clustering 0.727
Color Transition Smoothness 0.687
Transition Uniformity 0.8
Sharp Transition Ratio 0.1
Transition Directionality 0.042
Mean Saturation 0.294
Saturation Variance 0.047
Low Saturation Ratio 0.696
Medium Saturation Ratio 0.242
High Saturation Ratio 0.063
Saturation Clustering 0.999
Hue Concentration 0.894
Complementary Balance 0.0
Analogous Dominance 0.996
Temperature Bias 1.0

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). Bb Major - Research on Harmony - Variations 20 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1144.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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