AQC0712 | NAN-COL000242

Nanopublication — Computational Image Analysis - AQC0712

B Minor - Research on Harmony - Variation 2

Claim 1: Computational Image Analysis - AQC0712

Computational image analysis of artwork B Minor - Research on Harmony - Variation 2 (AQC0712) [1] by Arnaud Quercy [2], performed according to IDS-CMP-2025 [3], using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 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: 3024x4032 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 6DCCC3 34.6 green mediumaquamarine
2 CCC1AD 10.6 yellow-orange silver
3 2E333E 10.2 blue-violet grayish purple
4 130F16 9.6 black black
5 DFD2C0 7.6 yellow-orange lightgray
6 E8A45B 6.5 orange sandybrown
7 4A526D 6.3 blue-violet grayish purple
8 D69643 5.3 orange peru
9 5F6A39 5.2 yellow-green dark brown
10 798295 4.1 blue-violet grayish purple
11 621606 0.3 red-orange maroon [Accent]
12 AF9D27 0.3 yellow darkgoldenrod [Accent]
13 9EC4CF 0.3 blue lightsteelblue [Accent]
14 7FE3E9 0.3 blue-green skyblue [Accent]

Color Families:

Family %
green 34.6
blue-violet 20.6
yellow-orange 18.1
orange 11.9
black 9.6
yellow-green 5.2
red-orange 0.3
yellow 0.3
blue 0.3
blue-green 0.3

Accent Colors:

Hex Family Name Chroma
621606 red-orange maroon 43.3
AF9D27 yellow darkgoldenrod 59.3
9EC4CF blue lightsteelblue 14.1
7FE3E9 blue-green skyblue 30.5

B) Texture Analysis

Metric Value
Global Roughness 0.244
Mean Local Roughness 0.025
Roughness Uniformity 0.026
Edge Density 0.125
Mean Gradient Magnitude 0.193
Gradient Variance 0.073
Gradient Smoothness 0.0
Directional Coherence 0.016
Pattern Complexity 0.126
Pattern Repetition 1.0
Detail Frequency Ratio 0.648
Spatial Variation 0.182
Texture Consistency 0.312

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.549
Brightness Variance 0.244
Brightness Uniformity 0.554
Brightness Skewness -0.844
Brightness Entropy 7.191
Rms Contrast 0.244
Michelson Contrast 1.0
Weber Contrast 0.83
Mean Local Contrast 0.027
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.753
Shadow Percentage 24.139
Midtone Percentage 23.25
Highlight Percentage 52.611
Shadow Clipping 0.049
Highlight Clipping 0.003
Tonal Balance 0.0
Fine Contrast 0.014
Medium Contrast 0.033
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.193
Contrast Clustering 0.688

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.791
Color Clustering 0.801
Color Transition Smoothness 0.498
Transition Uniformity 0.471
Sharp Transition Ratio 0.1
Transition Directionality 0.024
Mean Saturation 0.39
Saturation Variance 0.031
Low Saturation Ratio 0.317
Medium Saturation Ratio 0.654
High Saturation Ratio 0.03
Saturation Clustering 0.997
Hue Concentration 0.404
Complementary Balance 0.101
Analogous Dominance 0.685
Temperature Bias -0.444

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). B Minor - Research on Harmony - Variation 2 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0712.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

Checksum (SHA-256)

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