AQC0716

Nanopublication — Computational Image Analysis - AQC0716

Claim 1: Computational Image Analysis - AQC0716

Computational image analysis [3] of artwork Bb Minor [1] - Research on Harmony - Variation 7 (AQC0716) [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]: 2977x3970 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 AB5579 19.4 red dusty mauve
2 9B436B 17.0 red indianred
3 94324A 15.7 red brown
4 BF6889 9.2 red dusty mauve
5 55302A 8.9 red-orange dark brown
6 3D1618 8.4 red-orange very dark red
7 A8CACA 8.0 blue-green lightsteelblue
8 EEB899 7.4 orange burlywood
9 87ABB9 4.3 blue steel gray
10 ECACC5 1.7 red lightpink
11 0D1727 0.3 blue-violet very dark gray [Accent]
12 D7E9E4 0.3 green white [Accent]
13 5E4061 0.3 red-violet dusty mauve [Accent]

Color Families:

Family %
red 63.0
red-orange 17.2
blue-green 8.0
orange 7.4
blue 4.3
blue-violet 0.3
green 0.3
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
0D1727 blue-violet very dark gray 12.2
D7E9E4 green white 7.0
5E4061 red-violet dusty mauve 23.6

Texture Analysis

Metric Value
Global Roughness 0.189
Mean Local Roughness 0.025
Roughness Uniformity 0.02
Edge Density 0.152
Mean Gradient Magnitude 0.196
Gradient Variance 0.043
Gradient Smoothness 0.0
Directional Coherence 0.009
Pattern Complexity 0.123
Pattern Repetition 1.0
Detail Frequency Ratio 0.655
Spatial Variation 0.145
Texture Consistency 0.6

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.443
Brightness Variance 0.189
Brightness Uniformity 0.573
Brightness Skewness 0.377
Brightness Entropy 7.362
Rms Contrast 0.189
Michelson Contrast 1.0
Weber Contrast 0.734
Mean Local Contrast 0.027
Contrast Uniformity 0.268
Dynamic Range 1.0
Effective Dynamic Range 0.631
Shadow Percentage 26.45
Midtone Percentage 55.072
Highlight Percentage 18.478
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.075
Fine Contrast 0.014
Medium Contrast 0.033
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.317
Edge Contrast 0.196
Contrast Clustering 0.4

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.742
Color Clustering 0.71
Color Transition Smoothness 0.51
Transition Uniformity 0.73
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.499
Saturation Variance 0.026
Low Saturation Ratio 0.13
Medium Saturation Ratio 0.798
High Saturation Ratio 0.072
Saturation Clustering 0.999
Hue Concentration 0.881
Complementary Balance 0.042
Analogous Dominance 0.958
Temperature Bias 0.916

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). Bb Minor - Research on Harmony - Variation 7 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0716.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/bb-minor-research-on-harmony-variation-7_7yo.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)

e76e9caddb81974fc8e42e794a5c9af46af023870495ca75f07851b56fdb917c