AQC0752

Nanopublication — Computational Image Analysis - AQC0752

by Arnaud Quercy · D Major - Research on Harmony - Variation 7 · 2024

Claim 1: Computational Image Analysis - AQC0752

Analysis record [3]: D Major [1] - Research on Harmony - Variation 7 (AQC0752) [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]: 2916x3888 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CA841A 21.3 orange darkgoldenrod
2 E4BE82 13.6 yellow-orange burlywood
3 D4A137 13.6 yellow-orange goldenrod
4 202221 12.3 gray very dark gray
5 B6B0A3 12.2 yellow-orange steel gray
6 363F34 9.6 yellow-green darkslategray
7 CCC3B7 7.5 yellow-orange silver
8 719583 4.3 yellow-green blue gray
9 A69262 3.8 yellow-orange ochre
10 4D814F 1.8 yellow-green seagreen
11 270601 0.3 red-orange very dark red [Accent]

Color Families:

Family %
yellow-orange 50.7
orange 21.3
yellow-green 15.6
gray 12.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
270601 red-orange very dark red 15.3

Texture Analysis

Metric Value
Global Roughness 0.216
Mean Local Roughness 0.016
Roughness Uniformity 0.014
Edge Density 0.084
Mean Gradient Magnitude 0.152
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.599
Spatial Variation 0.139
Texture Consistency 0.489

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.544
Brightness Variance 0.216
Brightness Uniformity 0.603
Brightness Skewness -0.842
Brightness Entropy 7.238
Rms Contrast 0.216
Michelson Contrast 1.0
Weber Contrast 0.781
Mean Local Contrast 0.019
Contrast Uniformity 0.138
Dynamic Range 1.0
Effective Dynamic Range 0.675
Shadow Percentage 21.719
Midtone Percentage 42.714
Highlight Percentage 35.567
Shadow Clipping 0.003
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.024
Coarse Contrast 0.04
Multiscale Contrast Ratio 0.197
Edge Contrast 0.152
Contrast Clustering 0.511

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.718
Color Clustering 0.64
Color Transition Smoothness 0.617
Transition Uniformity 0.79
Sharp Transition Ratio 0.1
Transition Directionality 0.013
Mean Saturation 0.438
Saturation Variance 0.101
Low Saturation Ratio 0.416
Medium Saturation Ratio 0.249
High Saturation Ratio 0.335
Saturation Clustering 0.999
Hue Concentration 0.854
Complementary Balance 0.003
Analogous Dominance 0.875
Temperature Bias 0.763

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). D Major - Research on Harmony - Variation 7 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0752.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major-research-on-harmony-variation-7_8co.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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