AQC0851

Nanopublication — Computational Image Analysis - AQC0851

Claim 1: Computational Image Analysis - AQC0851

Computational image analysis [3] of artwork C Major [1] - Research on Harmony - Variation 12 (AQC0851) [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 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]: 2331x3108 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D9D6C8 14.6 yellow lightgray
2 C74B25 14.2 red-orange chocolate
3 CAB8CE 12.8 red-violet thistle
4 DDD7DE 11.9 white gainsboro
5 DC6646 10.7 red-orange indianred
6 E190A8 9.0 red palevioletred
7 E7A6C1 8.9 red lightpink
8 BE9AB1 7.8 red-violet steel gray
9 D5737E 6.2 red-orange lightcoral
10 39252D 4.0 red very dark gray
11 4B4455 0.3 violet dusty mauve [Accent]

Color Families:

Family %
red-orange 31.1
red 22.0
red-violet 20.5
yellow 14.6
white 11.9
violet 0.3

Accent Colors:

Hex Family Name Chroma
4B4455 violet dusty mauve 11.4

Texture Analysis

Metric Value
Global Roughness 0.178
Mean Local Roughness 0.011
Roughness Uniformity 0.014
Edge Density 0.029
Mean Gradient Magnitude 0.1
Gradient Variance 0.024
Gradient Smoothness 0.0
Directional Coherence 0.062
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.604
Spatial Variation 0.129
Texture Consistency 0.516

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.657
Brightness Variance 0.178
Brightness Uniformity 0.729
Brightness Skewness -0.888
Brightness Entropy 7.147
Rms Contrast 0.178
Michelson Contrast 1.0
Weber Contrast 0.512
Mean Local Contrast 0.013
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.49
Shadow Percentage 3.916
Midtone Percentage 38.163
Highlight Percentage 57.921
Shadow Clipping 0.003
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.016
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.1
Contrast Clustering 0.484

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.743
Color Clustering 0.521
Color Transition Smoothness 0.747
Transition Uniformity 0.833
Sharp Transition Ratio 0.1
Transition Directionality 0.069
Mean Saturation 0.336
Saturation Variance 0.077
Low Saturation Ratio 0.544
Medium Saturation Ratio 0.272
High Saturation Ratio 0.185
Saturation Clustering 1.0
Hue Concentration 0.944
Complementary Balance 0.0
Analogous Dominance 0.983
Temperature Bias 0.988

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 Major - Research on Harmony - Variation 12 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0851.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/c-major-research-on-harmony-variation-12_9f6.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)

f99812561cbce0633f2b7518613783a2c63ae8e8fb0ea6b1aad39674fd3f6eb7