AQC0594

Nanopublication — Computational Image Analysis - AQC0594

by Arnaud Quercy · F minor - Research on Harmony · 2024

Claim 1: Computational Image Analysis - AQC0594

Analysis record [3]: F minor - Research [1] on Harmony (AQC0594) [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]: 2558x3411 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CDC7BB 41.5 yellow-orange silver
2 293D54 18.7 blue-violet grayish purple
3 D9D7D0 16.5 white lightgray
4 44576E 6.4 blue-violet grayish purple
5 451F2D 4.2 red very dark red
6 1B1015 3.4 red black
7 708299 2.9 blue-violet grayish purple
8 D69567 2.4 orange darksalmon
9 4895C3 2.1 blue steelblue
10 AE6633 1.9 orange burnt sienna
11 8C7771 0.3 red-orange gray [Accent]

Color Families:

Family %
yellow-orange 41.5
blue-violet 28.0
white 16.5
red 7.5
orange 4.3
blue 2.1
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
8C7771 red-orange gray 9.2

Texture Analysis

Metric Value
Global Roughness 0.272
Mean Local Roughness 0.028
Roughness Uniformity 0.042
Edge Density 0.087
Mean Gradient Magnitude 0.19
Gradient Variance 0.125
Gradient Smoothness 0.0
Directional Coherence 0.095
Pattern Complexity 0.123
Pattern Repetition 1.0
Detail Frequency Ratio 0.683
Spatial Variation 0.185
Texture Consistency 0.443

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.589
Brightness Variance 0.272
Brightness Uniformity 0.539
Brightness Skewness -0.605
Brightness Entropy 6.85
Rms Contrast 0.272
Michelson Contrast 1.0
Weber Contrast 0.77
Mean Local Contrast 0.027
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.698
Shadow Percentage 29.687
Midtone Percentage 11.301
Highlight Percentage 59.012
Shadow Clipping 0.018
Highlight Clipping 0.006
Tonal Balance 0.0
Fine Contrast 0.017
Medium Contrast 0.035
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.19
Contrast Clustering 0.557

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.761
Color Clustering 0.834
Color Transition Smoothness 0.496
Transition Uniformity 0.127
Sharp Transition Ratio 0.1
Transition Directionality 0.112
Mean Saturation 0.264
Saturation Variance 0.052
Low Saturation Ratio 0.609
Medium Saturation Ratio 0.364
High Saturation Ratio 0.027
Saturation Clustering 0.997
Hue Concentration 0.559
Complementary Balance 0.091
Analogous Dominance 0.749
Temperature Bias -0.483

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 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0594.html

[2] Quercy, A. (2024). F minor - Research on Harmony - Gallery. https://artquamanima.com/en/artworks/2024/01/f-minor-research-on-harmony_6n8.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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