AQC0963

Nanopublication — Computational Image Analysis - AQC0963

by Arnaud Quercy · G Minor - Research on harmony - Variation 16 · 2026

Claim 1: Computational Image Analysis - AQC0963

Analysis record [3]: G Minor [1] - Research on harmony - Variation 16 (AQC0963) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-03-05.

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]: 1937x2905 pixels. Analysis date: 2026-03-05.

Color Analysis

Rank Color Hex % Family Name
1 E08F71 21.0 orange darksalmon
2 D07E5F 14.3 orange peru
3 6C5B78 13.3 violet dusty mauve
4 B4B4B7 12.5 gray silver
5 121019 10.8 violet black
6 4E415A 7.4 violet dusty mauve
7 2C2C35 6.2 violet very dark gray
8 E5AF96 5.5 orange burlywood
9 8D7E92 5.3 red-violet dusty mauve
10 EAD4C6 3.7 orange wheat
11 67271D 0.3 red-orange russet [Accent]

Color Families:

Family %
orange 44.5
violet 37.7
gray 12.5
red-violet 5.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
67271D red-orange russet 35.0

Texture Analysis

Metric Value
Global Roughness 0.228
Mean Local Roughness 0.039
Roughness Uniformity 0.032
Edge Density 0.208
Mean Gradient Magnitude 0.287
Gradient Variance 0.099
Gradient Smoothness 0.0
Directional Coherence 0.01
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.679
Spatial Variation 0.186
Texture Consistency 0.622

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.499
Brightness Variance 0.228
Brightness Uniformity 0.543
Brightness Skewness -0.594
Brightness Entropy 7.534
Rms Contrast 0.228
Michelson Contrast 1.0
Weber Contrast 0.851
Mean Local Contrast 0.04
Contrast Uniformity 0.214
Dynamic Range 1.0
Effective Dynamic Range 0.722
Shadow Percentage 24.416
Midtone Percentage 50.727
Highlight Percentage 24.857
Shadow Clipping 0.001
Highlight Clipping 0.004
Tonal Balance 0.143
Fine Contrast 0.024
Medium Contrast 0.049
Coarse Contrast 0.062
Multiscale Contrast Ratio 0.381
Edge Contrast 0.287
Contrast Clustering 0.378

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.747
Color Clustering 0.796
Color Transition Smoothness 0.26
Transition Uniformity 0.333
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.334
Saturation Variance 0.035
Low Saturation Ratio 0.444
Medium Saturation Ratio 0.546
High Saturation Ratio 0.01
Saturation Clustering 0.997
Hue Concentration 0.541
Complementary Balance 0.011
Analogous Dominance 0.582
Temperature Bias 0.528

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 (2026). G Minor - Research on harmony - Variation 16 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0963.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2026/03/g-minor-research-on-harmony-variation-16_1ymm.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/10/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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