AQC0684

Nanopublication — Computational Image Analysis - AQC0684

by Arnaud Quercy · Tritone (D, G#) - Reflexions 18 · 2024

Claim 1: Computational Image Analysis - AQC0684

Analysis record [3]: Tritone [1] (D, G#) - Reflexions 18 (AQC0684) [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]: 2588x3451 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 DEBEA2 23.3 orange tan
2 DCCABE 16.4 orange lightgray
3 C2B3B2 13.1 red-orange silver
4 D68351 9.0 orange peru
5 A69898 8.8 red-orange steel gray
6 56555D 7.9 gray dusty mauve
7 DC9E7E 6.9 orange darksalmon
8 907569 6.5 orange gray
9 617689 4.9 blue-violet grayish purple
10 403637 3.1 red darkslategray
11 295364 0.3 blue darkslategray [Accent]
12 8285AA 0.3 violet dusty mauve [Accent]

Color Families:

Family %
orange 62.1
red-orange 21.9
gray 7.9
blue-violet 4.9
red 3.1
blue 0.3
violet 0.3

Accent Colors:

Hex Family Name Chroma
295364 blue darkslategray 16.6
8285AA violet dusty mauve 21.2

Texture Analysis

Metric Value
Global Roughness 0.164
Mean Local Roughness 0.01
Roughness Uniformity 0.014
Edge Density 0.029
Mean Gradient Magnitude 0.098
Gradient Variance 0.03
Gradient Smoothness 0.0
Directional Coherence 0.025
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.593
Spatial Variation 0.116
Texture Consistency 0.596

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.65
Brightness Variance 0.164
Brightness Uniformity 0.748
Brightness Skewness -1.037
Brightness Entropy 6.991
Rms Contrast 0.164
Michelson Contrast 1.0
Weber Contrast 0.527
Mean Local Contrast 0.012
Contrast Uniformity 0.0
Dynamic Range 0.965
Effective Dynamic Range 0.51
Shadow Percentage 6.399
Midtone Percentage 35.477
Highlight Percentage 58.124
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.015
Coarse Contrast 0.028
Multiscale Contrast Ratio 0.187
Edge Contrast 0.098
Contrast Clustering 0.404

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.733
Color Clustering 0.683
Color Transition Smoothness 0.744
Transition Uniformity 0.796
Sharp Transition Ratio 0.1
Transition Directionality 0.038
Mean Saturation 0.256
Saturation Variance 0.027
Low Saturation Ratio 0.704
Medium Saturation Ratio 0.284
High Saturation Ratio 0.012
Saturation Clustering 1.0
Hue Concentration 0.76
Complementary Balance 0.078
Analogous Dominance 0.879
Temperature Bias 0.769

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). Tritone (D, G#) - Reflexions 18 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0684.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/tritone-d-g-reflexions-18_7m8.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)

b94854ecbdb9bb3d0005fda549f8dd955e9bd8288bd9f255f703c66e4ab5098d