AQC0927

Nanopublication — Computational Image Analysis - AQC0927

Claim 1: Computational Image Analysis - AQC0927

The artwork Ab Major [1] - Research on Harmony - Variations 13 (AQC0927) [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]: 1932x2898 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 586876 18.1 blue grayish purple
2 658C9F 17.8 blue cadetblue
3 C2AEA5 12.1 orange steel gray
4 89A0AF 11.7 blue steel gray
5 7C848B 11.5 blue-violet grayish purple
6 F14B07 10.3 orange orangered
7 EAC48D 6.5 yellow-orange burlywood
8 BC402C 5.9 red-orange brown
9 54432F 4.4 yellow-orange dark brown
10 251410 1.6 red-orange very dark gray
11 FDEDB4 0.3 yellow moccasin [Accent]

Color Families:

Family %
blue 47.7
orange 22.4
blue-violet 11.5
yellow-orange 10.9
red-orange 7.5
yellow 0.3

Accent Colors:

Hex Family Name Chroma
FDEDB4 yellow moccasin 30.1

Texture Analysis

Metric Value
Global Roughness 0.146
Mean Local Roughness 0.027
Roughness Uniformity 0.027
Edge Density 0.143
Mean Gradient Magnitude 0.206
Gradient Variance 0.075
Gradient Smoothness 0.0
Directional Coherence 0.025
Pattern Complexity 0.128
Pattern Repetition 1.0
Detail Frequency Ratio 0.665
Spatial Variation 0.083
Texture Consistency 0.539

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.515
Brightness Variance 0.146
Brightness Uniformity 0.716
Brightness Skewness 0.091
Brightness Entropy 7.157
Rms Contrast 0.146
Michelson Contrast 1.0
Weber Contrast 0.503
Mean Local Contrast 0.029
Contrast Uniformity 0.042
Dynamic Range 1.0
Effective Dynamic Range 0.49
Shadow Percentage 7.677
Midtone Percentage 75.196
Highlight Percentage 17.127
Shadow Clipping 0.007
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.015
Medium Contrast 0.036
Coarse Contrast 0.046
Multiscale Contrast Ratio 0.33
Edge Contrast 0.206
Contrast Clustering 0.461

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.755
Color Clustering 0.175
Color Transition Smoothness 0.473
Transition Uniformity 0.488
Sharp Transition Ratio 0.1
Transition Directionality 0.031
Mean Saturation 0.369
Saturation Variance 0.072
Low Saturation Ratio 0.503
Medium Saturation Ratio 0.337
High Saturation Ratio 0.16
Saturation Clustering 0.999
Hue Concentration 0.127
Complementary Balance 0.308
Analogous Dominance 0.559
Temperature Bias -0.12

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). Ab Major - Research on Harmony - Variations 13 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0927.html

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

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/10/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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