AQC0733

Nanopublication — Computational Image Analysis - AQC0733

Claim 1: Computational Image Analysis - AQC0733

Analysis record [3]: E Major [1] - Research on Harmony - Variation 4 (AQC0733) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-02-04.

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]: 2972x3962 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 667891 15.0 blue-violet grayish purple
2 3A344C 15.0 violet dusty mauve
3 4F88D0 13.4 blue-violet steelblue
4 E5D5B7 13.3 yellow-orange wheat
5 312627 12.8 red-orange very dark gray
6 D5B78B 11.1 yellow-orange tan
7 4E5069 7.3 violet dusty mauve
8 B09A4B 4.6 yellow-orange peru
9 3955B0 3.8 violet darkslateblue
10 DCBF35 3.7 yellow-orange goldenrod
11 634313 0.3 orange russet [Accent]
12 D5D25E 0.3 yellow ochre [Accent]

Color Families:

Family %
yellow-orange 32.8
blue-violet 28.4
violet 26.0
red-orange 12.8
orange 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
634313 orange russet 34.2
D5D25E yellow ochre 58.7

Texture Analysis

Metric Value
Global Roughness 0.232
Mean Local Roughness 0.011
Roughness Uniformity 0.013
Edge Density 0.018
Mean Gradient Magnitude 0.089
Gradient Variance 0.022
Gradient Smoothness 0.0
Directional Coherence 0.042
Pattern Complexity 0.123
Pattern Repetition 1.0
Detail Frequency Ratio 0.608
Spatial Variation 0.181
Texture Consistency 0.408

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.477
Brightness Variance 0.232
Brightness Uniformity 0.513
Brightness Skewness 0.197
Brightness Entropy 7.351
Rms Contrast 0.232
Michelson Contrast 1.0
Weber Contrast 0.789
Mean Local Contrast 0.012
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.698
Shadow Percentage 33.973
Midtone Percentage 38.196
Highlight Percentage 27.831
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.055
Fine Contrast 0.006
Medium Contrast 0.015
Coarse Contrast 0.023
Multiscale Contrast Ratio 0.25
Edge Contrast 0.089
Contrast Clustering 0.592

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.796
Color Clustering 0.633
Color Transition Smoothness 0.762
Transition Uniformity 0.848
Sharp Transition Ratio 0.1
Transition Directionality 0.052
Mean Saturation 0.379
Saturation Variance 0.032
Low Saturation Ratio 0.449
Medium Saturation Ratio 0.493
High Saturation Ratio 0.059
Saturation Clustering 1.0
Hue Concentration 0.201
Complementary Balance 0.272
Analogous Dominance 0.551
Temperature Bias 0.057

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 (2024). E Major - Research on Harmony - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0733.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/e-major-research-on-harmony-variation-4_85a.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)

b5c5038a214f2d128b8922e752f70280d971967c7b009290350979675f38d5d0