AQC0865

Nanopublication — Computational Image Analysis - AQC0865

by Arnaud Quercy · G Major - Research on Harmony - Variation 9 · 2025

Claim 1: Computational Image Analysis - AQC0865

Analysis record [3]: G Major [1] - Research on Harmony - Variation 9 (AQC0865) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2025-11-24.

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]: 2200x2933 pixels. Analysis date: 2025-11-24.

Color Analysis

Rank Color Hex % Family Name
1 DF9348 18.5 orange peru
2 E2A260 17.8 orange sandybrown
3 D6750F 13.7 orange chocolate
4 DD882C 12.5 orange goldenrod
5 E9B377 12.5 orange burlywood
6 D4C6A3 8.7 yellow-orange tan
7 E2D6BF 6.7 yellow-orange wheat
8 A4AC7C 3.4 yellow-green ochre
9 8A8051 3.3 yellow dimgray
10 47382C 3.0 orange darkslategray
11 725752 0.3 red-orange dimgray [Accent]

Color Families:

Family %
orange 77.9
yellow-orange 15.4
yellow-green 3.4
yellow 3.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
725752 red-orange dimgray 12.2

Texture Analysis

Metric Value
Global Roughness 0.121
Mean Local Roughness 0.019
Roughness Uniformity 0.012
Edge Density 0.063
Mean Gradient Magnitude 0.145
Gradient Variance 0.022
Gradient Smoothness 0.0
Directional Coherence 0.003
Pattern Complexity 0.126
Pattern Repetition 1.0
Detail Frequency Ratio 0.618
Spatial Variation 0.045
Texture Consistency 0.522

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.648
Brightness Variance 0.121
Brightness Uniformity 0.813
Brightness Skewness -1.015
Brightness Entropy 6.834
Rms Contrast 0.121
Michelson Contrast 0.984
Weber Contrast 0.345
Mean Local Contrast 0.019
Contrast Uniformity 0.329
Dynamic Range 0.992
Effective Dynamic Range 0.349
Shadow Percentage 2.846
Midtone Percentage 52.089
Highlight Percentage 45.064
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.012
Medium Contrast 0.023
Coarse Contrast 0.034
Multiscale Contrast Ratio 0.346
Edge Contrast 0.145
Contrast Clustering 0.478

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.73
Color Clustering 0.414
Color Transition Smoothness 0.64
Transition Uniformity 0.849
Sharp Transition Ratio 0.1
Transition Directionality 0.002
Mean Saturation 0.58
Saturation Variance 0.056
Low Saturation Ratio 0.178
Medium Saturation Ratio 0.503
High Saturation Ratio 0.318
Saturation Clustering 0.999
Hue Concentration 0.982
Complementary Balance 0.0
Analogous Dominance 0.998
Temperature Bias 0.955

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 (2025). G Major - Research on Harmony - Variation 9 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0865.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/g-major-research-on-harmony-variation-9_9km.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)

9c9488175d5c66011f992b156860505d19a3887761914a268d7e22b64d527fb0