AQC0668 | NAN-COL000282

Nanopublication — Computational Image Analysis - AQC0668

C+ - Research on Harmony - Variation 2

Claim 1: Computational Image Analysis - AQC0668

K-means clustering (10 colors) performed on artwork C+ - Research on Harmony - Variation 2 (AQC0668) [1] by Arnaud Quercy [2] on 2025-10-03, according to IDS-CMP-2025 [3]. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

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: 2610x3480 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 C3C6C4 18.2 white silver
2 D7D8D8 17.7 white gainsboro
3 AFB1AC 14.9 gray steel gray
4 9C9D91 12.1 yellow-green steel gray
5 CFB57F 11.2 yellow-orange tan
6 C59549 7.4 yellow-orange peru
7 878B6B 7.0 yellow-green gray
8 312F2D 5.5 gray darkslategray
9 4D6B60 3.4 green dimgray
10 82602A 2.6 yellow-orange burnt sienna
11 241809 0.3 orange very dark gray [Accent]
12 A6AA5E 0.3 yellow ochre [Accent]
13 6F8890 0.3 blue blue gray [Accent]
14 6C868B 0.3 blue-green blue gray [Accent]
15 758697 0.3 blue-violet grayish purple [Accent]

Color Families:

Family %
white 35.9
yellow-orange 21.2
gray 20.4
yellow-green 19.2
green 3.4
orange 0.3
yellow 0.3
blue 0.3
blue-green 0.3
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
241809 orange very dark gray 10.4
A6AA5E yellow ochre 40.2
6F8890 blue blue gray 9.9
6C868B blue-green blue gray 10.0
758697 blue-violet grayish purple 11.2

B) Texture Analysis

Metric Value
Global Roughness 0.171
Mean Local Roughness 0.017
Roughness Uniformity 0.015
Edge Density 0.082
Mean Gradient Magnitude 0.154
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.009
Pattern Complexity 0.123
Pattern Repetition 1.0
Detail Frequency Ratio 0.597
Spatial Variation 0.085
Texture Consistency 0.631

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.665
Brightness Variance 0.171
Brightness Uniformity 0.743
Brightness Skewness -1.309
Brightness Entropy 7.17
Rms Contrast 0.171
Michelson Contrast 1.0
Weber Contrast 0.481
Mean Local Contrast 0.019
Contrast Uniformity 0.204
Dynamic Range 1.0
Effective Dynamic Range 0.612
Shadow Percentage 6.831
Midtone Percentage 33.433
Highlight Percentage 59.735
Shadow Clipping 0.006
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.009
Medium Contrast 0.024
Coarse Contrast 0.04
Multiscale Contrast Ratio 0.225
Edge Contrast 0.154
Contrast Clustering 0.369

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.73
Color Clustering 0.705
Color Transition Smoothness 0.614
Transition Uniformity 0.785
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.185
Saturation Variance 0.042
Low Saturation Ratio 0.743
Medium Saturation Ratio 0.228
High Saturation Ratio 0.029
Saturation Clustering 1.0
Hue Concentration 0.822
Complementary Balance 0.007
Analogous Dominance 0.89
Temperature Bias 0.639

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). C+ - Research on Harmony - Variation 2 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0668.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)

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