AQC0455

Nanopublication — Computational Image Analysis - AQC0455

by Arnaud Quercy · Tritone (C, F#) - Reflexions 7 · 2023

Claim 1: Computational Image Analysis - AQC0455

Analysis record [3]: Tritone [1] (C, F#) - Reflexions 7 (AQC0455) [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]: 794x1126 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 1B191E 25.9 gray black
2 303436 15.1 gray darkslategray
3 2D7C60 13.2 green seagreen
4 6D1923 11.6 red-orange maroon
5 479A7B 11.6 yellow-green mediumseagreen
6 4C5656 8.0 gray darkslategrey
7 B91F1F 4.8 red-orange firebrick
8 3CE3BE 3.7 green turquoise
9 73C7A6 3.1 yellow-green mediumaquamarine
10 BF424A 2.9 red-orange indianred
11 B9935C 0.3 yellow-orange peru [Accent]
12 88454F 0.3 red burnt sienna [Accent]

Color Families:

Family %
gray 49.1
red-orange 19.4
green 16.9
yellow-green 14.7
yellow-orange 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
B9935C yellow-orange peru 34.7
88454F red burnt sienna 30.8

Texture Analysis

Metric Value
Global Roughness 0.171
Mean Local Roughness 0.029
Roughness Uniformity 0.03
Edge Density 0.129
Mean Gradient Magnitude 0.188
Gradient Variance 0.064
Gradient Smoothness 0.0
Directional Coherence 0.016
Pattern Complexity 0.126
Pattern Repetition 1.0
Detail Frequency Ratio 0.674
Spatial Variation 0.106
Texture Consistency 0.625

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.288
Brightness Variance 0.171
Brightness Uniformity 0.406
Brightness Skewness 0.744
Brightness Entropy 7.232
Rms Contrast 0.171
Michelson Contrast 1.0
Weber Contrast 0.805
Mean Local Contrast 0.026
Contrast Uniformity 0.013
Dynamic Range 1.0
Effective Dynamic Range 0.557
Shadow Percentage 63.125
Midtone Percentage 33.291
Highlight Percentage 3.584
Shadow Clipping 0.006
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.019
Medium Contrast 0.034
Coarse Contrast 0.041
Multiscale Contrast Ratio 0.464
Edge Contrast 0.188
Contrast Clustering 0.375

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.733
Color Clustering 0.248
Color Transition Smoothness 0.491
Transition Uniformity 0.55
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.463
Saturation Variance 0.068
Low Saturation Ratio 0.337
Medium Saturation Ratio 0.441
High Saturation Ratio 0.223
Saturation Clustering 0.997
Hue Concentration 0.16
Complementary Balance 0.097
Analogous Dominance 0.519
Temperature Bias -0.164

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 (2023). Tritone (C, F#) - Reflexions 7 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0455.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/tritone-c-f-reflexions-7_556.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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