AQC0922

Nanopublication — Computational Image Analysis - AQC0922

Claim 1: Computational Image Analysis - AQC0922

The artwork C Minor [1] - Research on Harmony - Variations 14 (AQC0922) [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]: 1736x2604 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 E0CCBA 20.3 orange wheat
2 E85634 14.7 red-orange tomato
3 483E48 14.1 red-violet dusty mauve
4 D8BCA3 12.9 orange tan
5 A47EBE 11.2 violet dusty mauve
6 E9D8CE 10.8 orange gainsboro
7 615171 7.5 violet dusty mauve
8 BC733A 3.9 orange peru
9 E78978 2.6 red-orange darksalmon
10 2E191D 2.2 red very dark gray
11 FFFAE3 0.3 yellow lightyellow [Accent]
12 A89F8E 0.3 yellow-orange rosybrown [Accent]

Color Families:

Family %
orange 47.9
violet 18.6
red-orange 17.3
red-violet 14.1
red 2.2
yellow 0.3
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
FFFAE3 yellow lightyellow 12.2
A89F8E yellow-orange rosybrown 10.0

Texture Analysis

Metric Value
Global Roughness 0.223
Mean Local Roughness 0.025
Roughness Uniformity 0.029
Edge Density 0.096
Mean Gradient Magnitude 0.196
Gradient Variance 0.096
Gradient Smoothness 0.0
Directional Coherence 0.009
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.64
Spatial Variation 0.079
Texture Consistency 0.703

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.596
Brightness Variance 0.223
Brightness Uniformity 0.625
Brightness Skewness -0.377
Brightness Entropy 7.3
Rms Contrast 0.223
Michelson Contrast 1.0
Weber Contrast 0.684
Mean Local Contrast 0.027
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.627
Shadow Percentage 19.002
Midtone Percentage 36.35
Highlight Percentage 44.648
Shadow Clipping 0.0
Highlight Clipping 0.006
Tonal Balance 0.0
Fine Contrast 0.014
Medium Contrast 0.034
Coarse Contrast 0.049
Multiscale Contrast Ratio 0.28
Edge Contrast 0.196
Contrast Clustering 0.297

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.718
Color Clustering 0.656
Color Transition Smoothness 0.499
Transition Uniformity 0.338
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.332
Saturation Variance 0.058
Low Saturation Ratio 0.556
Medium Saturation Ratio 0.279
High Saturation Ratio 0.164
Saturation Clustering 0.999
Hue Concentration 0.652
Complementary Balance 0.0
Analogous Dominance 0.677
Temperature Bias 0.68

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 Minor - Research on Harmony - Variations 14 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0922.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/11/c-minor-research-on-harmony-variations-14_ihx.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)

a48285da878aec08c42f50530d4da56d3475eb783ed2d3f883bba4dec04d01ba