AQC0431

Nanopublication — Computational Image Analysis - AQC0431

Claim 1: Computational Image Analysis - AQC0431

Analysis record [3]: Parable [1] of the Senses (AQC0431) [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]: 1536x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CEBEAC 15.5 orange silver
2 AB8763 14.8 orange rosybrown
3 C8AE78 12.6 yellow-orange ochre
4 946046 12.5 orange burnt sienna
5 E2DAD5 12.1 white gainsboro
6 4A555B 8.5 blue darkslategray
7 6D757A 6.8 gray dimgray
8 733C25 6.7 orange russet
9 939C9B 6.3 gray steel gray
10 2A3235 4.3 gray darkslategrey
11 423C08 0.3 yellow dark brown [Accent]
12 972A1D 0.3 red-orange brown [Accent]
13 638BB2 0.3 blue-violet grayish purple [Accent]
14 571726 0.3 red very dark red [Accent]

Color Families:

Family %
orange 49.5
gray 17.3
yellow-orange 12.6
white 12.1
blue 8.5
yellow 0.3
red-orange 0.3
blue-violet 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
423C08 yellow dark brown 31.3
972A1D red-orange brown 55.6
638BB2 blue-violet grayish purple 25.2
571726 red very dark red 31.6

Texture Analysis

Metric Value
Global Roughness 0.2
Mean Local Roughness 0.022
Roughness Uniformity 0.016
Edge Density 0.138
Mean Gradient Magnitude 0.176
Gradient Variance 0.029
Gradient Smoothness 0.027
Directional Coherence 0.024
Pattern Complexity 0.132
Pattern Repetition 1.0
Detail Frequency Ratio 0.631
Spatial Variation 0.139
Texture Consistency 0.703

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.569
Brightness Variance 0.2
Brightness Uniformity 0.649
Brightness Skewness -0.17
Brightness Entropy 7.562
Rms Contrast 0.2
Michelson Contrast 1.0
Weber Contrast 0.643
Mean Local Contrast 0.023
Contrast Uniformity 0.346
Dynamic Range 1.0
Effective Dynamic Range 0.635
Shadow Percentage 13.879
Midtone Percentage 49.2
Highlight Percentage 36.921
Shadow Clipping 0.001
Highlight Clipping 0.001
Tonal Balance 0.331
Fine Contrast 0.013
Medium Contrast 0.029
Coarse Contrast 0.04
Multiscale Contrast Ratio 0.316
Edge Contrast 0.176
Contrast Clustering 0.297

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.718
Color Clustering 0.772
Color Transition Smoothness 0.544
Transition Uniformity 0.801
Sharp Transition Ratio 0.1
Transition Directionality 0.025
Mean Saturation 0.319
Saturation Variance 0.045
Low Saturation Ratio 0.491
Medium Saturation Ratio 0.463
High Saturation Ratio 0.046
Saturation Clustering 0.999
Hue Concentration 0.661
Complementary Balance 0.152
Analogous Dominance 0.841
Temperature Bias 0.691

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). Parable of the Senses — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0431.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/parable-of-the-senses_4vu.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)

0c690b13c7b26c4c7f6875f2b49a7a42bacb37bf27c593fee49bab9dadb3149a