AQC0815

Nanopublication — Computational Image Analysis - AQC0815

by Arnaud Quercy · C Octaves - Reflexions 35 · 2025

Claim 1: Computational Image Analysis - AQC0815

K-means clustering analysis [3] (10 colors) performed on artwork C Octaves [1] - Reflexions 35 (AQC0815) [2] by Arnaud Quercy [2] on 2026-02-04. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.

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]: 2328x3104 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E5AD90 29.8 orange burlywood
2 EEBA9F 16.2 orange tan
3 DA9C83 12.6 orange darksalmon
4 C5A791 11.4 orange rosybrown
5 B2917D 9.8 orange ochre
6 957662 5.4 orange gray
7 71584B 4.2 orange dimgray
8 CF594C 3.6 red-orange indianred
9 DC766A 3.5 red-orange lightcoral
10 46332D 3.3 red-orange darkslategray
11 FAC9D2 0.3 red pink [Accent]

Color Families:

Family %
orange 89.6
red-orange 10.4
red 0.3

Accent Colors:

Hex Family Name Chroma
FAC9D2 red pink 19.1

Texture Analysis

Metric Value
Global Roughness 0.135
Mean Local Roughness 0.023
Roughness Uniformity 0.02
Edge Density 0.128
Mean Gradient Magnitude 0.183
Gradient Variance 0.042
Gradient Smoothness 0.0
Directional Coherence 0.004
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.635
Spatial Variation 0.076
Texture Consistency 0.59

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.655
Brightness Variance 0.135
Brightness Uniformity 0.794
Brightness Skewness -1.606
Brightness Entropy 6.682
Rms Contrast 0.135
Michelson Contrast 1.0
Weber Contrast 0.401
Mean Local Contrast 0.024
Contrast Uniformity 0.191
Dynamic Range 1.0
Effective Dynamic Range 0.427
Shadow Percentage 4.267
Midtone Percentage 32.941
Highlight Percentage 62.792
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.013
Medium Contrast 0.03
Coarse Contrast 0.043
Multiscale Contrast Ratio 0.289
Edge Contrast 0.183
Contrast Clustering 0.41

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.732
Color Clustering 0.444
Color Transition Smoothness 0.545
Transition Uniformity 0.731
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.362
Saturation Variance 0.008
Low Saturation Ratio 0.221
Medium Saturation Ratio 0.773
High Saturation Ratio 0.006
Saturation Clustering 1.0
Hue Concentration 0.99
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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). C Octaves - Reflexions 35 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0815.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/c-octaves-reflexions-35_916.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)

f1c26f67140aca5c300e1f5ba7376cc12d1169b3cb02cc71850fe7c389d99893