AQC0745

Nanopublication — Computational Image Analysis - AQC0745

Claim 1: Computational Image Analysis - AQC0745

Analysis record [3]: C Major [1] - Research on Harmony - Variation 3 (AQC0745) [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]: 2953x3938 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 272024 21.2 red-violet very dark gray
2 CDC2B3 14.4 yellow-orange silver
3 B35B40 12.6 red-orange burnt sienna
4 D13635 9.8 red-orange crimson
5 A04A2D 9.7 orange burnt sienna
6 EEC9C8 9.1 red-orange pink
7 BDB0A0 8.4 yellow-orange steel gray
8 ED7A10 5.3 orange darkorange
9 C87362 5.2 red-orange indianred
10 443E44 4.3 red-violet dusty mauve
11 240309 0.3 red very dark red [Accent]
12 FCF5D4 0.3 yellow lightgoldenrodyellow [Accent]

Color Families:

Family %
red-orange 36.6
red-violet 25.6
yellow-orange 22.8
orange 15.0
red 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
240309 red very dark red 15.3
FCF5D4 yellow lightgoldenrodyellow 17.3

Texture Analysis

Metric Value
Global Roughness 0.241
Mean Local Roughness 0.017
Roughness Uniformity 0.016
Edge Density 0.089
Mean Gradient Magnitude 0.163
Gradient Variance 0.04
Gradient Smoothness 0.0
Directional Coherence 0.012
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.598
Spatial Variation 0.184
Texture Consistency 0.613

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.477
Brightness Variance 0.241
Brightness Uniformity 0.494
Brightness Skewness -0.006
Brightness Entropy 7.359
Rms Contrast 0.241
Michelson Contrast 1.0
Weber Contrast 0.833
Mean Local Contrast 0.021
Contrast Uniformity 0.095
Dynamic Range 1.0
Effective Dynamic Range 0.714
Shadow Percentage 25.9
Midtone Percentage 43.176
Highlight Percentage 30.924
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.048
Fine Contrast 0.009
Medium Contrast 0.026
Coarse Contrast 0.043
Multiscale Contrast Ratio 0.201
Edge Contrast 0.163
Contrast Clustering 0.387

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.768
Color Clustering 0.537
Color Transition Smoothness 0.578
Transition Uniformity 0.731
Sharp Transition Ratio 0.1
Transition Directionality 0.015
Mean Saturation 0.4
Saturation Variance 0.082
Low Saturation Ratio 0.545
Medium Saturation Ratio 0.218
High Saturation Ratio 0.237
Saturation Clustering 0.999
Hue Concentration 0.881
Complementary Balance 0.0
Analogous Dominance 0.93
Temperature Bias 0.934

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). C Major - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0745.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-major-research-on-harmony-variation-3_89y.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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