AQC0959

Nanopublication — Computational Image Analysis - AQC0959

Claim 1: Computational Image Analysis - AQC0959

The artwork A Minor [1] M7 - Research on Harmony (AQC0959) [2] by Arnaud Quercy [2] underwent comprehensive computational analysis [3] on 2026-03-05. Method: k-means clustering with 10 colors extracted. Metrics documented: color distribution, texture analysis, brightness/contrast, spatial patterns.

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]: 1846x2769 pixels. Analysis date: 2026-03-05.

Color Analysis

Rank Color Hex % Family Name
1 3F6EA3 13.9 blue-violet grayish purple
2 B8BBBA 13.8 gray silver
3 1E1F1D 12.7 gray very dark gray
4 E7BD2A 12.4 yellow-orange goldenrod
5 A4A7A8 12.0 gray steel gray
6 E4DEBE 9.8 yellow wheat
7 BED22B 8.6 yellow yellowgreen
8 303334 8.1 gray darkslategray
9 E9C080 5.6 yellow-orange burlywood
10 4C5253 3.2 gray darkslategrey
11 BBCB50 0.3 yellow-green ochre [Accent]
12 6E95B3 0.3 blue cadetblue [Accent]

Color Families:

Family %
gray 49.8
yellow 18.4
yellow-orange 18.0
blue-violet 13.9
yellow-green 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
BBCB50 yellow-green ochre 62.0
6E95B3 blue cadetblue 20.9

Texture Analysis

Metric Value
Global Roughness 0.254
Mean Local Roughness 0.026
Roughness Uniformity 0.022
Edge Density 0.128
Mean Gradient Magnitude 0.21
Gradient Variance 0.059
Gradient Smoothness 0.0
Directional Coherence 0.001
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.645
Spatial Variation 0.178
Texture Consistency 0.62

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.558
Brightness Variance 0.254
Brightness Uniformity 0.544
Brightness Skewness -0.603
Brightness Entropy 7.301
Rms Contrast 0.254
Michelson Contrast 0.992
Weber Contrast 0.828
Mean Local Contrast 0.029
Contrast Uniformity 0.2
Dynamic Range 0.996
Effective Dynamic Range 0.749
Shadow Percentage 23.36
Midtone Percentage 21.575
Highlight Percentage 55.065
Shadow Clipping 0.0
Highlight Clipping 0.006
Tonal Balance 0.0
Fine Contrast 0.014
Medium Contrast 0.036
Coarse Contrast 0.047
Multiscale Contrast Ratio 0.289
Edge Contrast 0.21
Contrast Clustering 0.38

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.791
Color Clustering 0.594
Color Transition Smoothness 0.454
Transition Uniformity 0.597
Sharp Transition Ratio 0.1
Transition Directionality 0.002
Mean Saturation 0.351
Saturation Variance 0.095
Low Saturation Ratio 0.563
Medium Saturation Ratio 0.229
High Saturation Ratio 0.209
Saturation Clustering 0.999
Hue Concentration 0.342
Complementary Balance 0.101
Analogous Dominance 0.659
Temperature Bias 0.139

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 (2026). A Minor M7 - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0959.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2026/03/a-minor-m7-research-on-harmony_1yl2.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)

25170ddbd026dd9cac54a866ed2e3770579a79e343250c745421a29478f7d837