AQC0892

Nanopublication — Computational Image Analysis - AQC0892

Claim 1: Computational Image Analysis - AQC0892

The artwork B Major [1] - Research on Harmony - Variations 8 (AQC0892) [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]: 1953x2930 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 CE8DB1 16.4 red-violet rosybrown
2 8EACD6 15.0 blue-violet skyblue
3 EDD8AA 14.4 yellow-orange wheat
4 BB7C9C 13.8 red palevioletred
5 E4B7C2 11.1 red thistle
6 544B32 9.9 yellow-orange dark brown
7 D0CBDE 9.7 violet lightgray
8 6E6C54 4.0 yellow dimgray
9 80B250 3.0 yellow-green yellowgreen
10 281C18 2.5 orange very dark gray
11 F9DADC 0.3 red-orange mistyrose [Accent]

Color Families:

Family %
red 25.0
yellow-orange 24.4
red-violet 16.4
blue-violet 15.0
violet 9.7
yellow 4.0
yellow-green 3.0
orange 2.5
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
F9DADC red-orange mistyrose 11.4

Texture Analysis

Metric Value
Global Roughness 0.185
Mean Local Roughness 0.022
Roughness Uniformity 0.023
Edge Density 0.101
Mean Gradient Magnitude 0.187
Gradient Variance 0.068
Gradient Smoothness 0.0
Directional Coherence 0.004
Pattern Complexity 0.128
Pattern Repetition 1.0
Detail Frequency Ratio 0.622
Spatial Variation 0.11
Texture Consistency 0.841

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.641
Brightness Variance 0.185
Brightness Uniformity 0.712
Brightness Skewness -0.954
Brightness Entropy 7.2
Rms Contrast 0.185
Michelson Contrast 1.0
Weber Contrast 0.62
Mean Local Contrast 0.025
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.604
Shadow Percentage 10.746
Midtone Percentage 42.015
Highlight Percentage 47.239
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.012
Medium Contrast 0.031
Coarse Contrast 0.049
Multiscale Contrast Ratio 0.242
Edge Contrast 0.187
Contrast Clustering 0.159

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.763
Color Clustering 0.727
Color Transition Smoothness 0.529
Transition Uniformity 0.544
Sharp Transition Ratio 0.1
Transition Directionality 0.009
Mean Saturation 0.301
Saturation Variance 0.014
Low Saturation Ratio 0.433
Medium Saturation Ratio 0.561
High Saturation Ratio 0.006
Saturation Clustering 0.999
Hue Concentration 0.457
Complementary Balance 0.057
Analogous Dominance 0.684
Temperature Bias 0.524

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). B Major - Research on Harmony - Variations 8 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0892.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/11/b-major-research-on-harmony-variations-8_i7g.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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