AQC0523

Nanopublication — Computational Image Analysis - AQC0523

Claim 1: Computational Image Analysis - AQC0523

Analysis record [3]: D Major9 - Research [1] on Harmony - Variation 3 (AQC0523) [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]: 2121x2828 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E1E0DC 25.6 white gainsboro
2 D2D0CC 14.6 white lightgray
3 6D6967 9.3 gray dimgray
4 8C5538 9.0 orange burnt sienna
5 B88E67 8.9 orange rosybrown
6 4D4E52 8.7 gray grayish purple
7 A47453 7.2 orange indianred
8 B0ADA8 5.9 gray steel gray
9 CCA984 5.7 orange tan
10 817D7A 4.9 gray gray
11 2E1D19 0.3 red-orange very dark gray [Accent]
12 2B2225 0.3 red very dark gray [Accent]
13 87A8B6 0.3 blue steel gray [Accent]

Color Families:

Family %
white 40.3
orange 30.8
gray 28.9
red-orange 0.3
red 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
2E1D19 red-orange very dark gray 10.0
2B2225 red very dark gray 5.0
87A8B6 blue steel gray 13.6

Texture Analysis

Metric Value
Global Roughness 0.208
Mean Local Roughness 0.023
Roughness Uniformity 0.024
Edge Density 0.13
Mean Gradient Magnitude 0.182
Gradient Variance 0.056
Gradient Smoothness 0.0
Directional Coherence 0.011
Pattern Complexity 0.131
Pattern Repetition 1.0
Detail Frequency Ratio 0.665
Spatial Variation 0.129
Texture Consistency 0.708

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.639
Brightness Variance 0.208
Brightness Uniformity 0.674
Brightness Skewness -0.193
Brightness Entropy 7.203
Rms Contrast 0.208
Michelson Contrast 0.992
Weber Contrast 0.597
Mean Local Contrast 0.025
Contrast Uniformity 0.01
Dynamic Range 0.996
Effective Dynamic Range 0.584
Shadow Percentage 6.365
Midtone Percentage 45.513
Highlight Percentage 48.122
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.013
Medium Contrast 0.031
Coarse Contrast 0.04
Multiscale Contrast Ratio 0.32
Edge Contrast 0.182
Contrast Clustering 0.292

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.741
Color Clustering 0.83
Color Transition Smoothness 0.54
Transition Uniformity 0.646
Sharp Transition Ratio 0.1
Transition Directionality 0.015
Mean Saturation 0.179
Saturation Variance 0.046
Low Saturation Ratio 0.705
Medium Saturation Ratio 0.294
High Saturation Ratio 0.001
Saturation Clustering 1.0
Hue Concentration 0.989
Complementary Balance 0.001
Analogous Dominance 0.999
Temperature Bias 0.998

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 Major9 - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0523.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major9-research-on-harmony-variation-3_5vm.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)

0070ad53195ddebd391cffcd0cc92351736fadb0839d689cb3cebe6361ed67ff