AQC0756

Nanopublication — Computational Image Analysis - AQC0756

by Arnaud Quercy · D Minor - Research on Harmony - Variation 3 · 2024

Claim 1: Computational Image Analysis - AQC0756

Analysis record [3]: D Minor [1] - Research on Harmony - Variation 3 (AQC0756) [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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 282424 17.5 gray very dark gray
2 E6932E 16.9 orange goldenrod
3 ECA043 13.1 orange sandybrown
4 CC9548 10.9 orange peru
5 B9792C 10.4 orange chocolate
6 E18016 8.3 orange darkorange
7 BEB4A7 7.4 yellow-orange steel gray
8 D9A968 6.2 yellow-orange darksalmon
9 A84A32 5.0 red-orange burnt sienna
10 8D3722 4.6 red-orange russet
11 6B633B 0.3 yellow dark brown [Accent]

Color Families:

Family %
orange 59.4
gray 17.5
yellow-orange 13.6
red-orange 9.5
yellow 0.3

Accent Colors:

Hex Family Name Chroma
6B633B yellow dark brown 24.2

Texture Analysis

Metric Value
Global Roughness 0.198
Mean Local Roughness 0.011
Roughness Uniformity 0.012
Edge Density 0.036
Mean Gradient Magnitude 0.109
Gradient Variance 0.025
Gradient Smoothness 0.0
Directional Coherence 0.028
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.591
Spatial Variation 0.168
Texture Consistency 0.304

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.518
Brightness Variance 0.198
Brightness Uniformity 0.618
Brightness Skewness -0.974
Brightness Entropy 6.855
Rms Contrast 0.198
Michelson Contrast 1.0
Weber Contrast 0.78
Mean Local Contrast 0.014
Contrast Uniformity 0.0
Dynamic Range 0.996
Effective Dynamic Range 0.584
Shadow Percentage 20.731
Midtone Percentage 58.769
Highlight Percentage 20.5
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.005
Medium Contrast 0.017
Coarse Contrast 0.03
Multiscale Contrast Ratio 0.183
Edge Contrast 0.109
Contrast Clustering 0.696

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.725
Color Clustering 0.431
Color Transition Smoothness 0.724
Transition Uniformity 0.84
Sharp Transition Ratio 0.1
Transition Directionality 0.035
Mean Saturation 0.578
Saturation Variance 0.09
Low Saturation Ratio 0.238
Medium Saturation Ratio 0.254
High Saturation Ratio 0.509
Saturation Clustering 1.0
Hue Concentration 0.989
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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 Minor - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0756.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-minor-research-on-harmony-variation-3_8e8.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)

b6bae0a50327a0de0c0f730e9aa2c1bb81d3bb695e3633cf9db1eb0d398874c5