AQC0929

Nanopublication — Computational Image Analysis - AQC0929

Claim 1: Computational Image Analysis - AQC0929

Computational image analysis [3] of artwork A Minor [1] - Research on Harmony - Variations 13 (AQC0929) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 2025-12-11.

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]: 1953x2929 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 D58F60 25.3 orange darksalmon
2 E3A777 24.1 orange burlywood
3 EDDCAD 15.9 yellow-orange wheat
4 4D453C 8.7 orange darkslategray
5 EE4924 7.0 red-orange orangered
6 E4ACA6 6.2 red-orange tan
7 E96142 6.1 red-orange tomato
8 BE3F43 2.7 red-orange brown
9 EBD43F 2.5 yellow goldenrod
10 3E180E 1.5 red-orange very dark red
11 A5717A 0.3 red gray [Accent]

Color Families:

Family %
orange 58.1
red-orange 23.5
yellow-orange 15.9
yellow 2.5
red 0.3

Accent Colors:

Hex Family Name Chroma
A5717A red gray 22.2

Texture Analysis

Metric Value
Global Roughness 0.176
Mean Local Roughness 0.018
Roughness Uniformity 0.024
Edge Density 0.058
Mean Gradient Magnitude 0.145
Gradient Variance 0.064
Gradient Smoothness 0.0
Directional Coherence 0.063
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.627
Spatial Variation 0.104
Texture Consistency 0.711

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.633
Brightness Variance 0.176
Brightness Uniformity 0.721
Brightness Skewness -0.795
Brightness Entropy 7.182
Rms Contrast 0.176
Michelson Contrast 1.0
Weber Contrast 0.608
Mean Local Contrast 0.02
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.608
Shadow Percentage 9.988
Midtone Percentage 40.832
Highlight Percentage 49.18
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.009
Medium Contrast 0.025
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.145
Contrast Clustering 0.289

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.754
Color Clustering 0.306
Color Transition Smoothness 0.639
Transition Uniformity 0.577
Sharp Transition Ratio 0.1
Transition Directionality 0.072
Mean Saturation 0.482
Saturation Variance 0.038
Low Saturation Ratio 0.232
Medium Saturation Ratio 0.608
High Saturation Ratio 0.16
Saturation Clustering 0.999
Hue Concentration 0.972
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). A Minor - Research on Harmony - Variations 13 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0929.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/11/a-minor-research-on-harmony-variations-13_ikg.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)

12d3e5869a8be9813441d4b939e1bb4497df7396a51237fd20020561f25805f6