AQC1126

Nanopublication — Computational Image Analysis - AQC1126

Bb Major - Research on Harmony - Variations 16

Claim 1: Computational Image Analysis - AQC1126

Analysis record: Bb Major - Research on Harmony - Variations 16 (AQC1126) [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 A49587 19.1 orange rosybrown
2 B5A795 17.9 yellow-orange steel gray
3 C4B6A4 17.7 yellow-orange tan
4 6C625D 13.6 orange dimgray
5 8C7C77 11.1 orange gray
6 574840 11.0 orange dark brown
7 0A0504 3.7 black black
8 401229 2.9 red very dark red
9 E5DED0 1.6 yellow-orange gainsboro
10 AA450A 1.3 orange russet

Color Families:

Family %
orange 56.0
yellow-orange 37.3
black 3.7
red 2.9

B) Texture Analysis

Metric Value
Global Roughness 0.191
Mean Local Roughness 0.022
Roughness Uniformity 0.014
Edge Density 0.083
Mean Gradient Magnitude 0.149
Gradient Variance 0.026
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.139
Pattern Repetition 1.0
Detail Frequency Ratio 0.646
Spatial Variation 0.131
Texture Consistency 0.587

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.529
Brightness Variance 0.191
Brightness Uniformity 0.639
Brightness Skewness -0.825
Brightness Entropy 7.269
Rms Contrast 0.191
Michelson Contrast 1.0
Weber Contrast 0.609
Mean Local Contrast 0.022
Contrast Uniformity 0.297
Dynamic Range 1.0
Effective Dynamic Range 0.62
Shadow Percentage 16.8
Midtone Percentage 53.549
Highlight Percentage 29.651
Shadow Clipping 0.005
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.015
Medium Contrast 0.026
Coarse Contrast 0.033
Multiscale Contrast Ratio 0.45
Edge Contrast 0.149
Contrast Clustering 0.413

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.715
Color Clustering 0.663
Color Transition Smoothness 0.621
Transition Uniformity 0.824
Sharp Transition Ratio 0.1
Transition Directionality 0.01
Mean Saturation 0.226
Saturation Variance 0.029
Low Saturation Ratio 0.876
Medium Saturation Ratio 0.083
High Saturation Ratio 0.042
Saturation Clustering 0.999
Hue Concentration 0.889
Complementary Balance 0.0
Analogous Dominance 0.952
Temperature Bias 0.992

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 16 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1126.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)

1162fc90e868faede0b5359966db7467ce884893e9ca052065887113be7d6760

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