AQC0870

Nanopublication — Computational Image Analysis - AQC0870

Claim 1: Computational Image Analysis - AQC0870

The artwork C Major [1] - Research on Harmony - Variations 13 (AQC0870) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2025-12-11. Method: k-means clustering with 10 colors extracted. Metrics documented: color distribution, texture analysis, brightness/contrast, spatial patterns.

Context

Analysis performed according to MMIDS-CMP-2025 [3] includes four metric categories: (1) Color distribution via k-means (10 colors), (2) Texture analysis using Haralick features, (3) Brightness and contrast measurements, (4) Spatial pattern characterization. Source image [5]: 1895x2843 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 CD8B6E 22.4 orange darksalmon
2 3C3433 17.4 gray darkslategray
3 DC9E91 15.2 red-orange tan
4 D23527 11.8 red-orange firebrick
5 DD5B5F 8.8 red-orange indianred
6 DB5E18 7.0 orange chocolate
7 E0CDCA 6.4 red-orange lightgray
8 E3B352 4.0 yellow-orange sandybrown
9 2B120F 3.7 red-orange very dark gray
10 8B4A34 3.1 red-orange burnt sienna
11 FBE36A 0.3 yellow khaki [Accent]
12 6B545B 0.3 red dimgray [Accent]

Color Families:

Family %
red-orange 49.1
orange 29.4
gray 17.4
yellow-orange 4.0
yellow 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
FBE36A yellow khaki 61.3
6B545B red dimgray 11.0

Texture Analysis

Metric Value
Global Roughness 0.202
Mean Local Roughness 0.021
Roughness Uniformity 0.02
Edge Density 0.081
Mean Gradient Magnitude 0.171
Gradient Variance 0.055
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.122
Pattern Repetition 1.0
Detail Frequency Ratio 0.618
Spatial Variation 0.11
Texture Consistency 0.758

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.502
Brightness Variance 0.202
Brightness Uniformity 0.597
Brightness Skewness -0.328
Brightness Entropy 7.442
Rms Contrast 0.202
Michelson Contrast 1.0
Weber Contrast 0.722
Mean Local Contrast 0.023
Contrast Uniformity 0.056
Dynamic Range 1.0
Effective Dynamic Range 0.627
Shadow Percentage 22.613
Midtone Percentage 55.14
Highlight Percentage 22.247
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.129
Fine Contrast 0.012
Medium Contrast 0.028
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.258
Edge Contrast 0.171
Contrast Clustering 0.242

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.727
Color Clustering 0.467
Color Transition Smoothness 0.564
Transition Uniformity 0.618
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.469
Saturation Variance 0.071
Low Saturation Ratio 0.288
Medium Saturation Ratio 0.486
High Saturation Ratio 0.226
Saturation Clustering 0.999
Hue Concentration 0.976
Complementary Balance 0.0
Analogous Dominance 0.999
Temperature Bias 1.0

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 Multimodal Institute's computational imaging systems.

References

[1] Arnaud Quercy (2025). C Major - Research on Harmony - Variations 13 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0870.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/11/c-major-research-on-harmony-variations-13_hzi.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/11/mmids-cmp-2025-computational-image-analysis-standard-dg1.html

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

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