AQC0961

Nanopublication — Computational Image Analysis - AQC0961

Claim 1: Computational Image Analysis - AQC0961

The artwork Eb7 - Research [1] on Harmony (AQC0961) [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 3C95CB 16.9 blue-violet steelblue
2 CCC8C1 13.5 white silver
3 98756F 11.1 red-orange gray
4 255F99 11.0 blue-violet grayish purple
5 1A1C21 10.4 gray very dark gray
6 B0AEAB 9.6 gray steel gray
7 353639 8.9 gray dusty mauve
8 53B6E2 8.4 blue mediumturquoise
9 EAE8DE 5.2 yellow white
10 5B5957 4.8 gray dimgray
11 7DD3EA 0.3 blue-green skyblue [Accent]
12 EBDAAC 0.3 yellow-orange wheat [Accent]

Color Families:

Family %
gray 33.8
blue-violet 27.9
white 13.5
red-orange 11.1
blue 8.4
yellow 5.2
blue-green 0.3
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
7DD3EA blue-green skyblue 27.6
EBDAAC yellow-orange wheat 25.0

Texture Analysis

Metric Value
Global Roughness 0.233
Mean Local Roughness 0.043
Roughness Uniformity 0.042
Edge Density 0.189
Mean Gradient Magnitude 0.33
Gradient Variance 0.177
Gradient Smoothness 0.0
Directional Coherence 0.002
Pattern Complexity 0.112
Pattern Repetition 1.0
Detail Frequency Ratio 0.666
Spatial Variation 0.136
Texture Consistency 0.744

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.498
Brightness Variance 0.233
Brightness Uniformity 0.531
Brightness Skewness -0.093
Brightness Entropy 7.769
Rms Contrast 0.233
Michelson Contrast 1.0
Weber Contrast 0.81
Mean Local Contrast 0.047
Contrast Uniformity 0.044
Dynamic Range 1.0
Effective Dynamic Range 0.753
Shadow Percentage 26.342
Midtone Percentage 46.15
Highlight Percentage 27.508
Shadow Clipping 0.005
Highlight Clipping 0.005
Tonal Balance 0.43
Fine Contrast 0.023
Medium Contrast 0.057
Coarse Contrast 0.072
Multiscale Contrast Ratio 0.32
Edge Contrast 0.33
Contrast Clustering 0.256

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.702
Color Clustering 0.696
Color Transition Smoothness 0.133
Transition Uniformity 0.0
Sharp Transition Ratio 0.1
Transition Directionality 0.002
Mean Saturation 0.348
Saturation Variance 0.092
Low Saturation Ratio 0.523
Medium Saturation Ratio 0.293
High Saturation Ratio 0.185
Saturation Clustering 0.998
Hue Concentration 0.576
Complementary Balance 0.052
Analogous Dominance 0.783
Temperature Bias -0.561

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). Eb7 - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0961.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2026/03/eb7-research-on-harmony_1ylu.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)

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