AQC0765 | NAN-COL000189

Nanopublication — Computational Image Analysis - AQC0765

A Major - Research on Harmony - Variation 4

Claim 1: Computational Image Analysis - AQC0765

Computational image analysis of artwork A Major - Research on Harmony - Variation 4 (AQC0765) [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: 2543x3815 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 989281 20.1 yellow gray
2 C58827 10.8 yellow-orange peru
3 1C1816 10.3 gray black
4 C7A47A 10.0 yellow-orange ochre
5 C77110 10.0 orange chocolate
6 B6AB9E 9.0 yellow-orange steel gray
7 CC9555 8.3 orange ochre
8 D7C9C0 8.2 orange lightgray
9 744D27 7.4 orange russet
10 468C9D 5.7 blue-green steelblue
11 4B0F01 0.3 red-orange very dark red [Accent]
12 6B8A94 0.3 blue blue gray [Accent]
13 657D79 0.3 green blue gray [Accent]
14 656C57 0.3 yellow-green dimgray [Accent]

Color Families:

Family %
orange 34.0
yellow-orange 29.8
yellow 20.1
gray 10.3
blue-green 5.7
red-orange 0.3
blue 0.3
green 0.3
yellow-green 0.3

Accent Colors:

Hex Family Name Chroma
4B0F01 red-orange very dark red 34.8
6B8A94 blue blue gray 12.0
657D79 green blue gray 10.0
656C57 yellow-green dimgray 13.0

B) Texture Analysis

Metric Value
Global Roughness 0.186
Mean Local Roughness 0.013
Roughness Uniformity 0.012
Edge Density 0.055
Mean Gradient Magnitude 0.142
Gradient Variance 0.033
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.108
Pattern Repetition 1.0
Detail Frequency Ratio 0.572
Spatial Variation 0.135
Texture Consistency 0.581

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.536
Brightness Variance 0.186
Brightness Uniformity 0.652
Brightness Skewness -1.091
Brightness Entropy 7.119
Rms Contrast 0.186
Michelson Contrast 1.0
Weber Contrast 0.734
Mean Local Contrast 0.017
Contrast Uniformity 0.055
Dynamic Range 1.0
Effective Dynamic Range 0.694
Shadow Percentage 13.873
Midtone Percentage 66.371
Highlight Percentage 19.756
Shadow Clipping 0.004
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.021
Coarse Contrast 0.041
Multiscale Contrast Ratio 0.145
Edge Contrast 0.142
Contrast Clustering 0.419

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.753
Color Clustering 0.632
Color Transition Smoothness 0.636
Transition Uniformity 0.771
Sharp Transition Ratio 0.1
Transition Directionality 0.017
Mean Saturation 0.415
Saturation Variance 0.097
Low Saturation Ratio 0.459
Medium Saturation Ratio 0.295
High Saturation Ratio 0.246
Saturation Clustering 1.0
Hue Concentration 0.793
Complementary Balance 0.037
Analogous Dominance 0.896
Temperature Bias 0.793

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). A Major - Research on Harmony - Variation 4 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0765.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)

ea7bfe9f4c84994b0a55b0ce77bc7c5702de0a8b1bc92bb26ef3e9f94a0582ac

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