AQC0598

Nanopublication — Computational Image Analysis - AQC0598

Claim 1: Computational Image Analysis - AQC0598

Analysis record [3]: F minor - Research [1] on Harmony - Variation 4 (AQC0598) [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]: 2660x3546 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 384450 16.5 blue-violet grayish purple
2 663439 15.7 red-orange russet
3 DBDBDA 15.3 white gainsboro
4 CFC5B0 14.6 yellow-orange silver
5 E6D8B8 13.3 yellow-orange wheat
6 095CCA 9.0 violet royalblue
7 2D252A 7.8 red-violet very dark gray
8 60A2C6 3.7 blue cadetblue
9 866D72 2.5 red gray
10 C97D3D 1.6 orange peru
11 74C1D4 0.3 blue-green skyblue [Accent]
12 F9F6EC 0.3 yellow white [Accent]

Color Families:

Family %
yellow-orange 28.0
blue-violet 16.5
red-orange 15.7
white 15.3
violet 9.0
red-violet 7.8
blue 3.7
red 2.5
orange 1.6
blue-green 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
74C1D4 blue-green skyblue 25.5
F9F6EC yellow white 5.1

Texture Analysis

Metric Value
Global Roughness 0.282
Mean Local Roughness 0.02
Roughness Uniformity 0.036
Edge Density 0.063
Mean Gradient Magnitude 0.155
Gradient Variance 0.111
Gradient Smoothness 0.0
Directional Coherence 0.103
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.645
Spatial Variation 0.204
Texture Consistency 0.594

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.526
Brightness Variance 0.282
Brightness Uniformity 0.464
Brightness Skewness 0.091
Brightness Entropy 7.052
Rms Contrast 0.282
Michelson Contrast 1.0
Weber Contrast 0.745
Mean Local Contrast 0.021
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.718
Shadow Percentage 44.826
Midtone Percentage 11.861
Highlight Percentage 43.313
Shadow Clipping 0.007
Highlight Clipping 0.044
Tonal Balance 0.0
Fine Contrast 0.011
Medium Contrast 0.027
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.155
Contrast Clustering 0.406

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.759
Color Clustering 0.727
Color Transition Smoothness 0.594
Transition Uniformity 0.269
Sharp Transition Ratio 0.1
Transition Directionality 0.111
Mean Saturation 0.321
Saturation Variance 0.075
Low Saturation Ratio 0.626
Medium Saturation Ratio 0.25
High Saturation Ratio 0.124
Saturation Clustering 0.999
Hue Concentration 0.169
Complementary Balance 0.096
Analogous Dominance 0.515
Temperature Bias 0.081

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). F minor - Research on Harmony - Variation 4 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0598.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/f-minor-research-on-harmony-variation-4_6os.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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