AQC0825 | NAN-COL000006

Nanopublication — Computational Image Analysis - AQC0825

E Major - Research on Harmony - Variation 6

Claim 1: Computational Image Analysis - AQC0825

Analysis record: E Major - Research on Harmony - Variation 6 (AQC0825) [1] by Arnaud Quercy [2], per IDS-CMP-2025 [3]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2025-10-03.

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: 2239x2985 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 D2D0C2 22.7 yellow lightgray
2 C5C5B3 19.0 yellow silver
3 D4D9E3 17.9 blue-violet gainsboro
4 B9CD89 8.7 yellow-green tan
5 A6A79F 6.6 gray steel gray
6 8F9084 6.6 yellow-green gray
7 434646 5.1 gray darkslategray
8 292C2B 4.9 gray very dark gray
9 A2BA7A 4.8 yellow-green darkseagreen
10 707464 3.7 yellow-green dimgray
11 F8D1B3 0.3 orange peachpuff [Accent]

Color Families:

Family %
yellow 41.7
yellow-green 23.7
blue-violet 17.9
gray 16.6
orange 0.3

Accent Colors:

Hex Family Name Chroma
F8D1B3 orange peachpuff 21.9

B) Texture Analysis

Metric Value
Global Roughness 0.19
Mean Local Roughness 0.013
Roughness Uniformity 0.015
Edge Density 0.051
Mean Gradient Magnitude 0.124
Gradient Variance 0.039
Gradient Smoothness 0.0
Directional Coherence 0.032
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.591
Spatial Variation 0.112
Texture Consistency 0.678

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.7
Brightness Variance 0.19
Brightness Uniformity 0.729
Brightness Skewness -1.636
Brightness Entropy 6.881
Rms Contrast 0.19
Michelson Contrast 1.0
Weber Contrast 0.583
Mean Local Contrast 0.015
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.643
Shadow Percentage 9.538
Midtone Percentage 16.514
Highlight Percentage 73.949
Shadow Clipping 0.002
Highlight Clipping 0.004
Tonal Balance 0.0
Fine Contrast 0.007
Medium Contrast 0.019
Coarse Contrast 0.035
Multiscale Contrast Ratio 0.19
Edge Contrast 0.124
Contrast Clustering 0.322

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.726
Color Clustering 0.901
Color Transition Smoothness 0.685
Transition Uniformity 0.74
Sharp Transition Ratio 0.1
Transition Directionality 0.039
Mean Saturation 0.128
Saturation Variance 0.011
Low Saturation Ratio 0.896
Medium Saturation Ratio 0.103
High Saturation Ratio 0.001
Saturation Clustering 1.0
Hue Concentration 0.921
Complementary Balance 0.016
Analogous Dominance 0.953
Temperature Bias 0.001

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. (2025). E Major - Research on Harmony - Variation 6 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0825.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/2025/09/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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